premise string | hypothesis string | label int64 |
|---|---|---|
| | Manu.Segmentation | Interact.Segmentation | Dice |
| --- | --- | --- | --- |
| LeftVentricle | RightVentricle | LeftAtrium | | | | Case1 | 157min46sec | 18min46sec | 0.90 | 0.90 | 0.89 |
| --- | --- | --- | --- | --- | --- |
| Case2 | 131min26sec | 13min45sec | 0.90 | 0.87 | 0.92 |
| Case3 | 88min29sec | 13min35sec | 0.91 | 0.84 | 0.93 | | 1 |
| | Manu.Segmentation | Interact.Segmentation | Dice |
| --- | --- | --- | --- |
| LeftVentricle | RightVentricle | LeftAtrium | | | | | Manu.Segmentation | Interact.Segmentation | Dice | | |
| --- | --- | --- | --- | --- | --- |
| User1 | User2 | User3 | | | |
| LeftEyeBall | 3min35sec | 2min | 0.85 | 0.88 | 0.84 |
| RightEyeBall | 3min25sec | 1min30sec | 0.87 | 0.94 | 0.87 |
| BrainStem | 9min2sec | 5min30sec | 0.86 | 0.85 | 0.80 |
| Mandible | 29min37sec | 10min15sec | 0.81 | 0.90 | 0.86 | | 0 |
| | Manu.Segmentation | Interact.Segmentation | Dice |
| --- | --- | --- | --- |
| LeftVentricle | RightVentricle | LeftAtrium | | | | Case1 | 157min46sec | 18min46sec | 0.90 | 0.90 | 0.89 |
| --- | --- | --- | --- | --- | --- |
| Case2 | 131min26sec | 13min45sec | 0.90 | 0.87 | 0.92 |
| Case3 | 88min29sec | 13min35sec | 0.91 | 0.84 | 0.93 | | 1 |
| | Manu.Segmentation | Interact.Segmentation | Dice |
| --- | --- | --- | --- |
| LeftVentricle | RightVentricle | LeftAtrium | | | | LeftEyeBall | 3min35sec | 2min | 0.85 | 0.88 | 0.84 |
| --- | --- | --- | --- | --- | --- |
| RightEyeBall | 3min25sec | 1min30sec | 0.87 | 0.94 | 0.87 |
| BrainStem | 9min2sec | 5min30sec | 0.86 | 0.85 | 0.80 |
| Mandible | 29min37sec | 10min15sec | 0.81 | 0.90 | 0.86 | | 0 |
| kakuro | magic | | | |
| --- | --- | --- | --- | --- |
| #instances | cutoff | #instances | cutoff | |
| 100 | 3600s | 40 | 3600s | |
| #solved | avg.time | #solved | avg.time | |
| argosmt-sbc | 40 | 2521s | 40 | 296s |
| argosmt-ibc | 94 | 464s | 40 | 226s |
| argosmt-bel | 99 | 196s | 40 | 198s | | | sugar | 100 | 91s | 40 | 57s |
| --- | --- | --- | --- | --- |
| mistral | 10 | 3305s | 39 | 111s |
| opturion | 55 | 2126s | 40 | 10s | | 1 |
| kakuro | magic | | | |
| --- | --- | --- | --- | --- |
| #instances | cutoff | #instances | cutoff | |
| 100 | 3600s | 40 | 3600s | |
| #solved | avg.time | #solved | avg.time | |
| argosmt-sbc | 40 | 2521s | 40 | 296s |
| argosmt-ibc | 94 | 464s | 40 | 226s |
| argosmt-bel | 99 | 196s | 40 | 198s | | | name | \|V\| | \|E\| | tw(G) | safeseparatorsfound | maxsubproblem | time(secs) |
| --- | --- | --- | --- | --- | --- | --- |
| ex181 | 109 | 732 | 18 | 18 | 89 | 0.078 |
| ex183 | 265 | 471 | 11 | 173 | 76 | 0.031 |
| ex185 | 237 | 793 | 14 | 142 | 52 | 0.046 |
| ex187 | 240 | 453 | 10 | 138 | 81 | 0.031 |
| ex189 | 178 | 4517 | 70 | 6 | 161 | 0.062 |
| ex191 | 492 | 1608 | 15 | 184 | 132 | 0.171 |
| ex193 | 1391 | 3012 | 10 | 791 | 119 | 3.17 |
| ex195 | 216 | 382 | 10 | 114 | 84 | 0.015 |
| ex197 | 303 | 1158 | 15 | 176 | 56 | 0.062 |
| ex199 | 310 | 537 | 9 | 157 | 131 | 0.046 | | 0 |
| kakuro | magic | | | |
| --- | --- | --- | --- | --- |
| #instances | cutoff | #instances | cutoff | |
| 100 | 3600s | 40 | 3600s | |
| #solved | avg.time | #solved | avg.time | |
| argosmt-sbc | 40 | 2521s | 40 | 296s |
| argosmt-ibc | 94 | 464s | 40 | 226s |
| argosmt-bel | 99 | 196s | 40 | 198s |
| sugar | 100 | 91s | 40 | 57s | | | mistral | 10 | 3305s | 39 | 111s |
| --- | --- | --- | --- | --- |
| opturion | 55 | 2126s | 40 | 10s | | 1 |
| kakuro | magic | | | |
| --- | --- | --- | --- | --- |
| #instances | cutoff | #instances | cutoff | |
| 100 | 3600s | 40 | 3600s | |
| #solved | avg.time | #solved | avg.time | |
| argosmt-sbc | 40 | 2521s | 40 | 296s |
| argosmt-ibc | 94 | 464s | 40 | 226s |
| argosmt-bel | 99 | 196s | 40 | 198s |
| sugar | 100 | 91s | 40 | 57s | | | ex193 | 1391 | 3012 | 10 | 791 | 119 | 3.17 |
| --- | --- | --- | --- | --- | --- | --- |
| ex195 | 216 | 382 | 10 | 114 | 84 | 0.015 |
| ex197 | 303 | 1158 | 15 | 176 | 56 | 0.062 |
| ex199 | 310 | 537 | 9 | 157 | 131 | 0.046 | | 0 |
| Dataset | ModularityG1 | ModularityG2 | SVM | N-Bayes | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| mic | mac | mic | mac | mic | mac | mic | mac | mic | |
| 20Newsgroups | 78.70 | 77.12 | 82.19 | 82.78 | 82.84 | 83.60 | 81.03 | | 84.23 | | | Reuters-21578 | 91.23 | 76.25 | 92.77 | 81.19 | 96.98 | 91.50 | 96.07 | | 85.24 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| WebKB4 | 80.66 | 78.92 | 85.24 | 84.74 | 89.68 | 88.39 | 83.52 | | 72.56 |
| TripAdvisor | 90.30 | 90.10 | 85.60 | 85.60 | | | | | | | 1 |
| Dataset | ModularityG1 | ModularityG2 | SVM | N-Bayes | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| mic | mac | mic | mac | mic | mac | mic | mac | mic | |
| 20Newsgroups | 78.70 | 77.12 | 82.19 | 82.78 | 82.84 | 83.60 | 81.03 | | 84.23 | | | kNN | SVM-RBF | DT | RF | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Dataset | AP | RE | AP | RE | AP | RE | AP | RE |
| Digits08 | 0.89 | 0.96 | 0.97 | 0.89 | 0.87 | 0.63 | 0.85 | 0.48 |
| Credit | 0.96 | 0.78 | 0.94 | 0.53 | 0.79 | 0.42 | 0.79 | 0.33 |
| Cancer | 0.99 | 0.99 | 0.99 | 0.99 | 0.97 | 0.89 | 0.99 | 0.98 |
| Qsar | 1 | 0.99 | 0.99 | 0.99 | 0.96 | 0.76 | 0.99 | 0.99 |
| Sonar | 0.99 | 0.98 | 1 | 1 | 0.97 | 0.62 | 0.99 | 0.95 |
| Theorem | 0.97 | 0.813 | 0.95 | 0.5 | 0.95 | 0.79 | 0.62 | 0.78 |
| Diabetes | 0.99 | 0.935 | 0.99 | 0.9 | 0.83 | 0.63 | 0.88 | 0.61 |
| Spambase | 0.93 | 0.99 | 0.48 | 0.84 | 0.08 | 0.11 | 0.99 | 0.98 |
| KDD99 | 0.99 | 0.93 | 1 | 0.99 | 0.89 | 0.54 | 0.92 | 0.27 |
| Captcha | 0.99 | 0.92 | 0.99 | 0.92 | 0.97 | 0.83 | 0.93 | 0.89 | | 0 |
| Dataset | ModularityG1 | ModularityG2 | SVM | N-Bayes | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| mic | mac | mic | mac | mic | mac | mic | mac | mic | |
| 20Newsgroups | 78.70 | 77.12 | 82.19 | 82.78 | 82.84 | 83.60 | 81.03 | | 84.23 |
| Reuters-21578 | 91.23 | 76.25 | 92.77 | 81.19 | 96.98 | 91.50 | 96.07 | | 85.24 | | | WebKB4 | 80.66 | 78.92 | 85.24 | 84.74 | 89.68 | 88.39 | 83.52 | | 72.56 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| TripAdvisor | 90.30 | 90.10 | 85.60 | 85.60 | | | | | | | 1 |
| Dataset | ModularityG1 | ModularityG2 | SVM | N-Bayes | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| mic | mac | mic | mac | mic | mac | mic | mac | mic | |
| 20Newsgroups | 78.70 | 77.12 | 82.19 | 82.78 | 82.84 | 83.60 | 81.03 | | 84.23 |
| Reuters-21578 | 91.23 | 76.25 | 92.77 | 81.19 | 96.98 | 91.50 | 96.07 | | 85.24 | | | Digits08 | 0.89 | 0.96 | 0.97 | 0.89 | 0.87 | 0.63 | 0.85 | 0.48 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Credit | 0.96 | 0.78 | 0.94 | 0.53 | 0.79 | 0.42 | 0.79 | 0.33 |
| Cancer | 0.99 | 0.99 | 0.99 | 0.99 | 0.97 | 0.89 | 0.99 | 0.98 |
| Qsar | 1 | 0.99 | 0.99 | 0.99 | 0.96 | 0.76 | 0.99 | 0.99 |
| Sonar | 0.99 | 0.98 | 1 | 1 | 0.97 | 0.62 | 0.99 | 0.95 |
| Theorem | 0.97 | 0.813 | 0.95 | 0.5 | 0.95 | 0.79 | 0.62 | 0.78 |
| Diabetes | 0.99 | 0.935 | 0.99 | 0.9 | 0.83 | 0.63 | 0.88 | 0.61 |
| Spambase | 0.93 | 0.99 | 0.48 | 0.84 | 0.08 | 0.11 | 0.99 | 0.98 |
| KDD99 | 0.99 | 0.93 | 1 | 0.99 | 0.89 | 0.54 | 0.92 | 0.27 |
| Captcha | 0.99 | 0.92 | 0.99 | 0.92 | 0.97 | 0.83 | 0.93 | 0.89 | | 0 |
| Object | Method | MaxF1 | Runtime[s] |
| --- | --- | --- | --- |
| Chef<br>(28940) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.13<br>0.22<br>0.67<br>0.64<br>0.85 | -<br>0.012<br>1.7<br>1.9<br>0.33 |
| Para<br>(16732) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.11<br>0.15<br>0.57<br>0.54<br>0.71 | -<br>0.0058<br>0.64<br>0.77<br>0.16 | | | T-rex<br>(15851) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.10<br>0.11<br>0.56<br>0.47<br>0.78 | -<br>0.0051<br>0.56<br>0.65<br>0.13 |
| --- | --- | --- | --- |
| Chicken<br>(12324) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.14<br>0.18<br>0.59<br>0.56<br>0.80 | -<br>0.0039<br>0.35<br>0.41<br>0.11 | | 1 |
| Object | Method | MaxF1 | Runtime[s] |
| --- | --- | --- | --- |
| Chef<br>(28940) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.13<br>0.22<br>0.67<br>0.64<br>0.85 | -<br>0.012<br>1.7<br>1.9<br>0.33 |
| Para<br>(16732) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.11<br>0.15<br>0.57<br>0.54<br>0.71 | -<br>0.0058<br>0.64<br>0.77<br>0.16 | | | Method | Adapt | BBN | | |
| --- | --- | --- | --- | --- |
| Ma-F1 | Mi-F1 | Acc. | | |
| FIGER<br>HYENA<br>WSABIE<br>HLE<br>ProtoLE<br>Proto-HLE | NA<br>NA<br>NA<br>Y<br>N<br>Y<br>N<br>Y<br>N | 67.28<br>51.38<br>71.28<br>70.84<br>68.86<br>72.67<br>75.78<br>71.97<br>74.54 | 60.70<br>52.85<br>72.08<br>71.61<br>70.00<br>73.54<br>76.50<br>72.89<br>74.38 | 46.92<br>45.01<br>66.22<br>65.74<br>63.32<br>67.58<br>70.43<br>67.05<br>69.46 |
| | | OntoNotes | | |
| FIGER<br>HYENA<br>WSABIE<br>HLE<br>ProtoLE<br>Proto-HLE | NA<br>NA<br>NA<br>Y<br>N<br>Y<br>N<br>Y<br>N | 58.77<br>47.65<br>62.03<br>61.54<br>59.52<br>60.90<br>65.91<br>62.71<br>68.23 | 52.37<br>43.97<br>55.83<br>49.16<br>54.01<br>54.68<br>59.08<br>56.64<br>61.27 | 38.01<br>26.56<br>43.61<br>43.25<br>41.60<br>42.82<br>46.94<br>44.81<br>49.30 |
| | | Wiki | | |
| FIGER<br>HYENA<br>WSABIE<br>HLE<br>ProtoLE<br>Proto-HLE | NA<br>NA<br>NA<br>Y<br>N<br>Y<br>N<br>Y<br>N | 68.28<br>45.51<br>67.97<br>67.09<br>65.29<br>66.96<br>68.06<br>67.85<br>66.61 | 64.71<br>43.80<br>64.49<br>65.65<br>62.53<br>65.78<br>66.53<br>65.74<br>65.29 | 47.37<br>30.67<br>48.28<br>47.01<br>45.19<br>49.18<br>53.54<br>50.27<br>50.45 | | 0 |
| Object | Method | MaxF1 | Runtime[s] |
| --- | --- | --- | --- |
| Chef<br>(28940) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.13<br>0.22<br>0.67<br>0.64<br>0.85 | -<br>0.012<br>1.7<br>1.9<br>0.33 |
| Para<br>(16732) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.11<br>0.15<br>0.57<br>0.54<br>0.71 | -<br>0.0058<br>0.64<br>0.77<br>0.16 | | | T-rex<br>(15851) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.10<br>0.11<br>0.56<br>0.47<br>0.78 | -<br>0.0051<br>0.56<br>0.65<br>0.13 |
| --- | --- | --- | --- |
| Chicken<br>(12324) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.14<br>0.18<br>0.59<br>0.56<br>0.80 | -<br>0.0039<br>0.35<br>0.41<br>0.11 | | 1 |
| Object | Method | MaxF1 | Runtime[s] |
| --- | --- | --- | --- |
| Chef<br>(28940) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.13<br>0.22<br>0.67<br>0.64<br>0.85 | -<br>0.012<br>1.7<br>1.9<br>0.33 |
| Para<br>(16732) | Ldistance2<br>Ratio<br>GC<br>GC+RANSAC<br>Voting | 0.11<br>0.15<br>0.57<br>0.54<br>0.71 | -<br>0.0058<br>0.64<br>0.77<br>0.16 | | | FIGER<br>HYENA<br>WSABIE<br>HLE<br>ProtoLE<br>Proto-HLE | NA<br>NA<br>NA<br>Y<br>N<br>Y<br>N<br>Y<br>N | 58.77<br>47.65<br>62.03<br>61.54<br>59.52<br>60.90<br>65.91<br>62.71<br>68.23 | 52.37<br>43.97<br>55.83<br>49.16<br>54.01<br>54.68<br>59.08<br>56.64<br>61.27 | 38.01<br>26.56<br>43.61<br>43.25<br>41.60<br>42.82<br>46.94<br>44.81<br>49.30 |
| --- | --- | --- | --- | --- |
| | | Wiki | | |
| FIGER<br>HYENA<br>WSABIE<br>HLE<br>ProtoLE<br>Proto-HLE | NA<br>NA<br>NA<br>Y<br>N<br>Y<br>N<br>Y<br>N | 68.28<br>45.51<br>67.97<br>67.09<br>65.29<br>66.96<br>68.06<br>67.85<br>66.61 | 64.71<br>43.80<br>64.49<br>65.65<br>62.53<br>65.78<br>66.53<br>65.74<br>65.29 | 47.37<br>30.67<br>48.28<br>47.01<br>45.19<br>49.18<br>53.54<br>50.27<br>50.45 | | 0 |
| | Citeseernetwork | Coranetwork | | |
| --- | --- | --- | --- | --- |
| | F1 | Accuracy | F1 | Accuracy |
| MF | 0.6291 | 0.7267 | 0.7970 | 0.8261 | | | LBP | 0.6264 | 0.7294 | 0.8248 | 0.8449 |
| --- | --- | --- | --- | --- |
| Stacked | - | 0.598 | - | 0.739 |
| SBSN | 0.6705 | 0.7029 | 0.8420 | 0.8519 | | 1 |
| | Citeseernetwork | Coranetwork | | |
| --- | --- | --- | --- | --- |
| | F1 | Accuracy | F1 | Accuracy |
| MF | 0.6291 | 0.7267 | 0.7970 | 0.8261 | | | | Wordsnetwork | |
| --- | --- | --- |
| | F1measure | Accuracy |
| wvRN | 0.4216 | 0.5289 |
| MRF | 0.4411 | 0.4614 |
| SBSN | 0.7462 | 0.7484 | | 0 |
| | Citeseernetwork | Coranetwork | | |
| --- | --- | --- | --- | --- |
| | F1 | Accuracy | F1 | Accuracy |
| MF | 0.6291 | 0.7267 | 0.7970 | 0.8261 | | | LBP | 0.6264 | 0.7294 | 0.8248 | 0.8449 |
| --- | --- | --- | --- | --- |
| Stacked | - | 0.598 | - | 0.739 |
| SBSN | 0.6705 | 0.7029 | 0.8420 | 0.8519 | | 1 |
| | Citeseernetwork | Coranetwork | | |
| --- | --- | --- | --- | --- |
| | F1 | Accuracy | F1 | Accuracy |
| MF | 0.6291 | 0.7267 | 0.7970 | 0.8261 | | | wvRN | 0.4216 | 0.5289 |
| --- | --- | --- |
| MRF | 0.4411 | 0.4614 |
| SBSN | 0.7462 | 0.7484 | | 0 |
| Methods | aeroplane | bicycle | boat | bottle | bus | car | chair | diningtable | motorbike | sofa | train | tvmonitor | Average |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| ObjectDetection(AP) | | | | | | | | | | | | | |
| DPM | 42.2 | 49.6 | 6.0 | 20.0 | 54.1 | 38.3 | 15.0 | 9.0 | 33.1 | 18.9 | 36.4 | 33.2 | 29.6 |
| R-CNN | 72.4 | 68.7 | 34.0 | – | 73.0 | 62.3 | 33.0 | 35.2 | 70.7 | 49.6 | 70.1 | 57.2 | 56.9 |
| Oursw/oExtra | 76.3 | 73.4 | 43.4 | 44.7 | 74.5 | 63.3 | 35.4 | 32.4 | 74.9 | 51.9 | 74.1 | 60.9 | 58.8 |
| OursFull | 76.5 | 74.0 | 42.4 | 47.0 | 74.5 | 64.7 | 38.5 | 38.6 | 76.7 | 55.1 | 74.8 | 65.3 | 60.7 |
| JointObjectDetectionandPoseEstimation(4ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 34.6 | 41.7 | 1.5 | – | 26.1 | 20.2 | 6.8 | 3.1 | 30.4 | 5.1 | 10.7 | 34.7 | 19.5 |
| DPM-VOC+VP | 39.4 | 43.9 | 0.3 | – | 49.1 | 37.6 | 6.1 | 3.0 | 32.2 | 11.8 | 12.5 | 33.2 | 24.5 |
| Oursw/oExtra | 62.3 | 56.6 | 18.0 | – | 62.0 | 40.9 | 19.3 | 14.9 | 62.3 | 44.1 | 58.1 | 58.5 | 45.2 |
| OursFull | 61.4 | 60.4 | 21.1 | – | 63.0 | 48.7 | 23.8 | 17.4 | 60.7 | 47.8 | 55.9 | 62.3 | 47.5 |
| JointObjectDetectionandPoseEstimation(8ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 23.4 | 36.5 | 1.0 | – | 35.5 | 23.5 | 5.8 | 3.6 | 25.1 | 12.5 | 10.9 | 27.4 | 18.7 |
| DPM-VOC+VP | 29.7 | 42.6 | 0.4 | – | 39.5 | 36.8 | 9.4 | 2.6 | 32.9 | 11.0 | 10.3 | 28.6 | 22.2 |
| Oursw/oExtra | 45.9 | 25.5 | 11.1 | – | 37.7 | 34.6 | 15.2 | 7.4 | 37.1 | 33.0 | 42.5 | 24.3 | 28.6 | | | OursFull | 48.8 | 36.3 | 16.4 | – | 39.8 | 37.2 | 19.1 | 13.2 | 37.0 | 32.1 | 44.4 | 26.9 | 31.9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| JointObjectDetectionandPoseEstimation(16ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 15.4 | 18.4 | 0.5 | – | 46.9 | 18.1 | 6.0 | 2.2 | 16.1 | 10.0 | 22.1 | 16.3 | 15.6 |
| DPM-VOC+VP | 17.0 | 24.7 | 1.0 | – | 49.0 | 30.1 | 6.6 | 3.0 | 17.2 | 7.7 | 20.4 | 20.2 | 17.9 |
| Oursw/oExtra | 23.3 | 19.2 | 8.4 | – | 52.6 | 27.0 | 9.9 | 5.1 | 23.6 | 20.9 | 27.4 | 27.9 | 22.3 |
| OursFull | 28.0 | 23.7 | 10.7 | – | 50.8 | 31.4 | 14.3 | 9.4 | 23.4 | 19.5 | 30.7 | 27.8 | 24.5 |
| JointObjectDetectionandPoseEstimation(24ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 8.0 | 14.3 | 0.3 | – | 39.2 | 13.7 | 4.4 | 3.6 | 10.1 | 8.2 | 20.0 | 11.2 | 12.1 |
| DPM-VOC+VP | 10.6 | 16.7 | 2.2 | – | 43.5 | 25.4 | 4.4 | 2.3 | 11.3 | 4.9 | 22.4 | 14.4 | 14.4 |
| Oursw/oExtra | 18.9 | 10.5 | 6.7 | – | 34.3 | 23.3 | 8.3 | 6.5 | 20.6 | 17.5 | 33.8 | 17.0 | 17.9 |
| OursFull | 20.7 | 16.4 | 7.9 | – | 34.6 | 24.6 | 9.4 | 7.6 | 19.9 | 20.0 | 32.7 | 18.2 | 19.3 | | 1 |
| Methods | aeroplane | bicycle | boat | bottle | bus | car | chair | diningtable | motorbike | sofa | train | tvmonitor | Average |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| ObjectDetection(AP) | | | | | | | | | | | | | |
| DPM | 42.2 | 49.6 | 6.0 | 20.0 | 54.1 | 38.3 | 15.0 | 9.0 | 33.1 | 18.9 | 36.4 | 33.2 | 29.6 |
| R-CNN | 72.4 | 68.7 | 34.0 | – | 73.0 | 62.3 | 33.0 | 35.2 | 70.7 | 49.6 | 70.1 | 57.2 | 56.9 |
| Oursw/oExtra | 76.3 | 73.4 | 43.4 | 44.7 | 74.5 | 63.3 | 35.4 | 32.4 | 74.9 | 51.9 | 74.1 | 60.9 | 58.8 |
| OursFull | 76.5 | 74.0 | 42.4 | 47.0 | 74.5 | 64.7 | 38.5 | 38.6 | 76.7 | 55.1 | 74.8 | 65.3 | 60.7 |
| JointObjectDetectionandPoseEstimation(4ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 34.6 | 41.7 | 1.5 | – | 26.1 | 20.2 | 6.8 | 3.1 | 30.4 | 5.1 | 10.7 | 34.7 | 19.5 |
| DPM-VOC+VP | 39.4 | 43.9 | 0.3 | – | 49.1 | 37.6 | 6.1 | 3.0 | 32.2 | 11.8 | 12.5 | 33.2 | 24.5 |
| Oursw/oExtra | 62.3 | 56.6 | 18.0 | – | 62.0 | 40.9 | 19.3 | 14.9 | 62.3 | 44.1 | 58.1 | 58.5 | 45.2 |
| OursFull | 61.4 | 60.4 | 21.1 | – | 63.0 | 48.7 | 23.8 | 17.4 | 60.7 | 47.8 | 55.9 | 62.3 | 47.5 |
| JointObjectDetectionandPoseEstimation(8ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 23.4 | 36.5 | 1.0 | – | 35.5 | 23.5 | 5.8 | 3.6 | 25.1 | 12.5 | 10.9 | 27.4 | 18.7 |
| DPM-VOC+VP | 29.7 | 42.6 | 0.4 | – | 39.5 | 36.8 | 9.4 | 2.6 | 32.9 | 11.0 | 10.3 | 28.6 | 22.2 |
| Oursw/oExtra | 45.9 | 25.5 | 11.1 | – | 37.7 | 34.6 | 15.2 | 7.4 | 37.1 | 33.0 | 42.5 | 24.3 | 28.6 | | | Methods | aero | bicycle | boat | bus | car | chair | table | mbike | sofa | train |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| VDPM | 34.6 | 41.7 | 1.5 | 26.1 | 20.2 | 6.8 | 3.1 | 30.4 | 5.1 | 10.7 |
| DPM-VOC+VP | 37.4 | 43.9 | 0.3 | 48.6 | 36.9 | 6.1 | 2.1 | 31.8 | 11.8 | 11.1 |
| RCNN+Alex | 54.0 | 50.5 | 15.1 | 57.1 | 41.8 | 15.7 | 18.6 | 50.8 | 28.4 | 46.1 |
| VpKps | 63.1 | 59.4 | 23.0 | 69.8 | 55.2 | 25.1 | 24.3 | 61.1 | 43.8 | 59.4 |
| OursShare300 | 63.6 | 54.7 | 25.0 | 67.7 | 47.3 | 10.8 | 38.5 | 59.4 | 41.8 | 65.0 |
| OursShare500 | 64.6 | 62.1 | 26.8 | 70.0 | 51.4 | 11.3 | 40.7 | 62.7 | 40.6 | 65.9 |
| VDPM | 23.4 | 36.5 | 1.0 | 35.5 | 23.5 | 5.8 | 3.6 | 25.1 | 12.5 | 10.9 |
| DPM-VOC+VP | 28.6 | 40.3 | 0.2 | 38.0 | 36.6 | 9.4 | 2.6 | 32.0 | 11.0 | 9.8 |
| RCNN+Alex | 44.5 | 41.1 | 10.1 | 48.0 | 36.6 | 13.7 | 15.1 | 39.9 | 26.8 | 39.1 |
| VpKps | 57.5 | 54.8 | 18.9 | 59.4 | 51.5 | 24.7 | 20.5 | 59.5 | 43.7 | 53.3 |
| OursShare300 | 57.6 | 50.8 | 20.9 | 58.4 | 43.1 | 9.1 | 34.2 | 52.3 | 37.2 | 55.6 |
| OursShare500 | 58.6 | 56.4 | 19.9 | 62.4 | 45.2 | 10.6 | 34.7 | 58.6 | 38.8 | 61.2 |
| VDPM | 15.4 | 18.4 | 0.5 | 46.9 | 18.1 | 6.0 | 2.2 | 16.1 | 10.0 | 22.1 |
| DPM-VOC+VP | 15.9 | 22.9 | 0.3 | 49.0 | 29.6 | 6.1 | 2.3 | 16.7 | 7.1 | 20.2 |
| RCNN+Alex | 27.5 | 25.8 | 6.5 | 45.8 | 29.7 | 8.5 | 12.0 | 31.4 | 17.7 | 29.7 |
| VpKps | 46.6 | 42.0 | 12.7 | 64.6 | 42.7 | 20.8 | 18.5 | 38.8 | 33.5 | 42.5 |
| OursShare300 | 45.4 | 33.4 | 13.7 | 52.9 | 32.9 | 5.3 | 27.2 | 38.8 | 27.3 | 37.4 |
| OursShare500 | 45.9 | 39.6 | 14.0 | 54.0 | 35.4 | 7.4 | 26.4 | 40.4 | 29.2 | 41.5 |
| VDPM | 8.0 | 14.3 | 0.3 | 39.2 | 13.7 | 4.4 | 3.6 | 10.1 | 8.2 | 20.0 |
| DPM-VOC+VP | 9.7 | 16.7 | 2.2 | 42.1 | 24.6 | 4.2 | 2.1 | 10.5 | 4.1 | 20.7 |
| RCNN+Alex | 21.5 | 22.0 | 4.1 | 38.6 | 25.5 | 7.4 | 11.0 | 24.4 | 15.0 | 28.0 |
| VpKps | 37.0 | 33.4 | 10.0 | 54.1 | 40.0 | 17.5 | 19.9 | 34.3 | 28.9 | 43.9 |
| OursShare300 | 35.7 | 23.6 | 10.8 | 51.7 | 33.8 | 6.2 | 23.6 | 26.9 | 20.4 | 46.9 |
| OursShare500 | 33.4 | 29.4 | 9.2 | 54.7 | 35.7 | 5.5 | 22.9 | 30.3 | 27.5 | 44.1 | | 0 |
| Methods | aeroplane | bicycle | boat | bottle | bus | car | chair | diningtable | motorbike | sofa | train | tvmonitor | Average |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| ObjectDetection(AP) | | | | | | | | | | | | | |
| DPM | 42.2 | 49.6 | 6.0 | 20.0 | 54.1 | 38.3 | 15.0 | 9.0 | 33.1 | 18.9 | 36.4 | 33.2 | 29.6 |
| R-CNN | 72.4 | 68.7 | 34.0 | – | 73.0 | 62.3 | 33.0 | 35.2 | 70.7 | 49.6 | 70.1 | 57.2 | 56.9 |
| Oursw/oExtra | 76.3 | 73.4 | 43.4 | 44.7 | 74.5 | 63.3 | 35.4 | 32.4 | 74.9 | 51.9 | 74.1 | 60.9 | 58.8 |
| OursFull | 76.5 | 74.0 | 42.4 | 47.0 | 74.5 | 64.7 | 38.5 | 38.6 | 76.7 | 55.1 | 74.8 | 65.3 | 60.7 |
| JointObjectDetectionandPoseEstimation(4ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 34.6 | 41.7 | 1.5 | – | 26.1 | 20.2 | 6.8 | 3.1 | 30.4 | 5.1 | 10.7 | 34.7 | 19.5 |
| DPM-VOC+VP | 39.4 | 43.9 | 0.3 | – | 49.1 | 37.6 | 6.1 | 3.0 | 32.2 | 11.8 | 12.5 | 33.2 | 24.5 | | | Oursw/oExtra | 62.3 | 56.6 | 18.0 | – | 62.0 | 40.9 | 19.3 | 14.9 | 62.3 | 44.1 | 58.1 | 58.5 | 45.2 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| OursFull | 61.4 | 60.4 | 21.1 | – | 63.0 | 48.7 | 23.8 | 17.4 | 60.7 | 47.8 | 55.9 | 62.3 | 47.5 |
| JointObjectDetectionandPoseEstimation(8ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 23.4 | 36.5 | 1.0 | – | 35.5 | 23.5 | 5.8 | 3.6 | 25.1 | 12.5 | 10.9 | 27.4 | 18.7 |
| DPM-VOC+VP | 29.7 | 42.6 | 0.4 | – | 39.5 | 36.8 | 9.4 | 2.6 | 32.9 | 11.0 | 10.3 | 28.6 | 22.2 |
| Oursw/oExtra | 45.9 | 25.5 | 11.1 | – | 37.7 | 34.6 | 15.2 | 7.4 | 37.1 | 33.0 | 42.5 | 24.3 | 28.6 |
| OursFull | 48.8 | 36.3 | 16.4 | – | 39.8 | 37.2 | 19.1 | 13.2 | 37.0 | 32.1 | 44.4 | 26.9 | 31.9 |
| JointObjectDetectionandPoseEstimation(16ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 15.4 | 18.4 | 0.5 | – | 46.9 | 18.1 | 6.0 | 2.2 | 16.1 | 10.0 | 22.1 | 16.3 | 15.6 |
| DPM-VOC+VP | 17.0 | 24.7 | 1.0 | – | 49.0 | 30.1 | 6.6 | 3.0 | 17.2 | 7.7 | 20.4 | 20.2 | 17.9 |
| Oursw/oExtra | 23.3 | 19.2 | 8.4 | – | 52.6 | 27.0 | 9.9 | 5.1 | 23.6 | 20.9 | 27.4 | 27.9 | 22.3 |
| OursFull | 28.0 | 23.7 | 10.7 | – | 50.8 | 31.4 | 14.3 | 9.4 | 23.4 | 19.5 | 30.7 | 27.8 | 24.5 |
| JointObjectDetectionandPoseEstimation(24ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 8.0 | 14.3 | 0.3 | – | 39.2 | 13.7 | 4.4 | 3.6 | 10.1 | 8.2 | 20.0 | 11.2 | 12.1 |
| DPM-VOC+VP | 10.6 | 16.7 | 2.2 | – | 43.5 | 25.4 | 4.4 | 2.3 | 11.3 | 4.9 | 22.4 | 14.4 | 14.4 |
| Oursw/oExtra | 18.9 | 10.5 | 6.7 | – | 34.3 | 23.3 | 8.3 | 6.5 | 20.6 | 17.5 | 33.8 | 17.0 | 17.9 |
| OursFull | 20.7 | 16.4 | 7.9 | – | 34.6 | 24.6 | 9.4 | 7.6 | 19.9 | 20.0 | 32.7 | 18.2 | 19.3 | | 1 |
| Methods | aeroplane | bicycle | boat | bottle | bus | car | chair | diningtable | motorbike | sofa | train | tvmonitor | Average |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| ObjectDetection(AP) | | | | | | | | | | | | | |
| DPM | 42.2 | 49.6 | 6.0 | 20.0 | 54.1 | 38.3 | 15.0 | 9.0 | 33.1 | 18.9 | 36.4 | 33.2 | 29.6 |
| R-CNN | 72.4 | 68.7 | 34.0 | – | 73.0 | 62.3 | 33.0 | 35.2 | 70.7 | 49.6 | 70.1 | 57.2 | 56.9 |
| Oursw/oExtra | 76.3 | 73.4 | 43.4 | 44.7 | 74.5 | 63.3 | 35.4 | 32.4 | 74.9 | 51.9 | 74.1 | 60.9 | 58.8 |
| OursFull | 76.5 | 74.0 | 42.4 | 47.0 | 74.5 | 64.7 | 38.5 | 38.6 | 76.7 | 55.1 | 74.8 | 65.3 | 60.7 |
| JointObjectDetectionandPoseEstimation(4ViewsAVP) | | | | | | | | | | | | | |
| VDPM | 34.6 | 41.7 | 1.5 | – | 26.1 | 20.2 | 6.8 | 3.1 | 30.4 | 5.1 | 10.7 | 34.7 | 19.5 |
| DPM-VOC+VP | 39.4 | 43.9 | 0.3 | – | 49.1 | 37.6 | 6.1 | 3.0 | 32.2 | 11.8 | 12.5 | 33.2 | 24.5 | | | RCNN+Alex | 21.5 | 22.0 | 4.1 | 38.6 | 25.5 | 7.4 | 11.0 | 24.4 | 15.0 | 28.0 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| VpKps | 37.0 | 33.4 | 10.0 | 54.1 | 40.0 | 17.5 | 19.9 | 34.3 | 28.9 | 43.9 |
| OursShare300 | 35.7 | 23.6 | 10.8 | 51.7 | 33.8 | 6.2 | 23.6 | 26.9 | 20.4 | 46.9 |
| OursShare500 | 33.4 | 29.4 | 9.2 | 54.7 | 35.7 | 5.5 | 22.9 | 30.3 | 27.5 | 44.1 | | 0 |
| Offset<br>∆m | Theoretical<br>time[s] | Experimental<br>time[s] | Speedup |
| --- | --- | --- | --- |
| 0 | 6.136 | 6.140 | 1.000 |
| 4 | 5.731 | 5.681 | 1.081 | | | 8 | 5.809 | 5.806 | 1.058 |
| --- | --- | --- | --- |
| 12 | 5.543 | 5.453 | 1.126 |
| 16 | 5.509 | 5.418 | 1.133 |
| 20 | 5.499 | 5.338 | 1.150 |
| 24 | 5.624 | 5.477 | 1.121 | | 1 |
| Offset<br>∆m | Theoretical<br>time[s] | Experimental<br>time[s] | Speedup |
| --- | --- | --- | --- |
| 0 | 6.136 | 6.140 | 1.000 |
| 4 | 5.731 | 5.681 | 1.081 | | | Offset<br>∆m | Theoretical<br>time[s] | Experimental<br>time[s] | Speedup |
| --- | --- | --- | --- |
| 0 | 1.486 | 1.548 | 1.000 |
| 4 | 1.470 | 1.470 | 1.053 |
| 6 | 1.401 | 1.374 | 1.127 |
| 7 | 1.422 | 1.361 | 1.137 |
| 8 | 1.386 | 1.364 | 1.135 |
| 9 | 1.398 | 1.348 | 1.148 |
| 10 | 1.397 | 1.352 | 1.145 |
| 11 | 1.429 | 1.372 | 1.129 |
| 12 | 1.402 | 1.368 | 1.131 | | 0 |
| Offset<br>∆m | Theoretical<br>time[s] | Experimental<br>time[s] | Speedup |
| --- | --- | --- | --- |
| 0 | 6.136 | 6.140 | 1.000 |
| 4 | 5.731 | 5.681 | 1.081 |
| 8 | 5.809 | 5.806 | 1.058 |
| 12 | 5.543 | 5.453 | 1.126 |
| 16 | 5.509 | 5.418 | 1.133 | | | 20 | 5.499 | 5.338 | 1.150 |
| --- | --- | --- | --- |
| 24 | 5.624 | 5.477 | 1.121 | | 1 |
| Offset<br>∆m | Theoretical<br>time[s] | Experimental<br>time[s] | Speedup |
| --- | --- | --- | --- |
| 0 | 6.136 | 6.140 | 1.000 |
| 4 | 5.731 | 5.681 | 1.081 |
| 8 | 5.809 | 5.806 | 1.058 |
| 12 | 5.543 | 5.453 | 1.126 |
| 16 | 5.509 | 5.418 | 1.133 | | | 6 | 1.401 | 1.374 | 1.127 |
| --- | --- | --- | --- |
| 7 | 1.422 | 1.361 | 1.137 |
| 8 | 1.386 | 1.364 | 1.135 |
| 9 | 1.398 | 1.348 | 1.148 |
| 10 | 1.397 | 1.352 | 1.145 |
| 11 | 1.429 | 1.372 | 1.129 |
| 12 | 1.402 | 1.368 | 1.131 | | 0 |
| Size | Stage1 | Stage2 | Stage3 | Stage4 | Stage5 |
| --- | --- | --- | --- | --- | --- |
| 50000 | 0.9999 | 0.9999 | 0.9999 | 0.9999 | 0.9996 | | | 40000 | 0.9999 | 0.9999 | 0.9999 | 0.9999 | 0.9993 |
| --- | --- | --- | --- | --- | --- |
| 30000 | 0.9999 | 0.9999 | 0.9999 | 0.9999 | 0.9988 |
| 20000 | 0.9999 | 0.9999 | 0.9999 | 0.9996 | 0.9972 |
| 10000 | 0.9999 | 0.9999 | 0.9997 | 0.9992 | 0.9945 | | 1 |
| Size | Stage1 | Stage2 | Stage3 | Stage4 | Stage5 |
| --- | --- | --- | --- | --- | --- |
| 50000 | 0.9999 | 0.9999 | 0.9999 | 0.9999 | 0.9996 | | | Set<br>Label | Non-Temporal | Temporal | | | |
| --- | --- | --- | --- | --- | --- |
| ROP | Stage1 | Stage2 | Stage1 | Stage2 | |
| Instruction-levelEvents | | | | | |
| I-0 | 0.301 | 0.876 | 0.767 | 0.981 | 0.806 |
| I-1 | 0.303 | 0.848 | 0.800 | 0.986 | 0.877 |
| I-2 | 0.314 | 0.836 | 0.776 | 0.958 | 0.820 |
| MicroarchitecturalEvents | | | | | |
| M-0 | 0.806 | 0.836 | 0.854 | 0.884 | 0.865 |
| M-1 | 0.504 | 0.728 | 0.644 | 0.974 | 0.786 |
| M-2 | 0.538 | 0.595 | 0.601 | 0.945 | 0.805 |
| BothInstruction-levelandMicroarchitecturalEvents | | | | | |
| AM-0 | 0.720 | 0.950 | 0.919 | 0.977 | 0.917 |
| AM-1 | 0.678 | 0.916 | 0.781 | 0.995 | 0.823 |
| AM-2 | 0.504 | 0.864 | 0.848 | 0.993 | 0.919 | | 0 |
| Size | Stage1 | Stage2 | Stage3 | Stage4 | Stage5 |
| --- | --- | --- | --- | --- | --- |
| 50000 | 0.9999 | 0.9999 | 0.9999 | 0.9999 | 0.9996 |
| 40000 | 0.9999 | 0.9999 | 0.9999 | 0.9999 | 0.9993 | | | 30000 | 0.9999 | 0.9999 | 0.9999 | 0.9999 | 0.9988 |
| --- | --- | --- | --- | --- | --- |
| 20000 | 0.9999 | 0.9999 | 0.9999 | 0.9996 | 0.9972 |
| 10000 | 0.9999 | 0.9999 | 0.9997 | 0.9992 | 0.9945 | | 1 |
| Size | Stage1 | Stage2 | Stage3 | Stage4 | Stage5 |
| --- | --- | --- | --- | --- | --- |
| 50000 | 0.9999 | 0.9999 | 0.9999 | 0.9999 | 0.9996 |
| 40000 | 0.9999 | 0.9999 | 0.9999 | 0.9999 | 0.9993 | | | I-0 | 0.301 | 0.876 | 0.767 | 0.981 | 0.806 |
| --- | --- | --- | --- | --- | --- |
| I-1 | 0.303 | 0.848 | 0.800 | 0.986 | 0.877 |
| I-2 | 0.314 | 0.836 | 0.776 | 0.958 | 0.820 |
| MicroarchitecturalEvents | | | | | |
| M-0 | 0.806 | 0.836 | 0.854 | 0.884 | 0.865 |
| M-1 | 0.504 | 0.728 | 0.644 | 0.974 | 0.786 |
| M-2 | 0.538 | 0.595 | 0.601 | 0.945 | 0.805 |
| BothInstruction-levelandMicroarchitecturalEvents | | | | | |
| AM-0 | 0.720 | 0.950 | 0.919 | 0.977 | 0.917 |
| AM-1 | 0.678 | 0.916 | 0.781 | 0.995 | 0.823 |
| AM-2 | 0.504 | 0.864 | 0.848 | 0.993 | 0.919 | | 0 |
| Size | Methods |
| --- | --- |
| 200 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| 450 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| 632 | inv-DAKR<br>bi-DAKR<br>re-ranking | | | 1025 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| --- | --- |
| 12180 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| 19732 | inv-DAKR<br>bi-DAKR<br>re-ranking | | 1 |
| Size | Methods |
| --- | --- |
| 200 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| 450 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| 632 | inv-DAKR<br>bi-DAKR<br>re-ranking | | | Methods | r=1 | r=5 | r=20 |
| --- | --- | --- | --- |
| k-NN<br>inv-DAKR<br>bi-DAKR<br>re-ranking | 65.51<br>66.77<br>66.57<br>67.68 | 81.72<br>82.68<br>82.88<br>82.17 | 90.10<br>91.21<br>91.46<br>90.91 |
| k-NN<br>inv-DAKR<br>bi-DAKR<br>re-ranking | 64.95<br>65.15<br>66.36<br>67.17 | 81.01<br>82.58<br>82.63<br>81.41 | 89.90<br>90.56<br>91.67<br>90.25 |
| k-NN<br>inv-DAKR<br>bi-DAKR<br>re-ranking | 63.33<br>63.89<br>65.15<br>65.71 | 80.51<br>80.81<br>81.67<br>80.51 | 88.74<br>89.65<br>91.01<br>89.29 |
| k-NN<br>inv-DAKR<br>bi-DAKR<br>re-ranking | 60.81<br>61.92<br>61.81<br>63.59 | 77.93<br>78.38<br>79.14<br>78.43 | 87.88<br>88.28<br>88.69<br>88.18 | | 0 |
| Size | Methods |
| --- | --- |
| 200 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| 450 | inv-DAKR<br>bi-DAKR<br>re-ranking | | | 632 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| --- | --- |
| 1025 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| 12180 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| 19732 | inv-DAKR<br>bi-DAKR<br>re-ranking | | 1 |
| Size | Methods |
| --- | --- |
| 200 | inv-DAKR<br>bi-DAKR<br>re-ranking |
| 450 | inv-DAKR<br>bi-DAKR<br>re-ranking | | | k-NN<br>inv-DAKR<br>bi-DAKR<br>re-ranking | 63.33<br>63.89<br>65.15<br>65.71 | 80.51<br>80.81<br>81.67<br>80.51 | 88.74<br>89.65<br>91.01<br>89.29 |
| --- | --- | --- | --- |
| k-NN<br>inv-DAKR<br>bi-DAKR<br>re-ranking | 60.81<br>61.92<br>61.81<br>63.59 | 77.93<br>78.38<br>79.14<br>78.43 | 87.88<br>88.28<br>88.69<br>88.18 | | 0 |
| -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 |
| -classe1820(attendus=169,ramenes=258.00,corrects=29.00)<br>rappel=0.172precision=0.112f-mesure=0.136 |
| -classe1830(attendus=169,ramenes=358.00,corrects=36.00)<br>rappel=0.213precision=0.101f-mesure=0.137 |
| -classe1840(attendus=169,ramenes=86.00,corrects=10.00)<br>rappel=0.059precision=0.116f-mesure=0.078 | | | -classe1850(attendus=169,ramenes=186.00,corrects=16.00)<br>rappel=0.095precision=0.086f-mesure=0.090 |
| --- |
| -classe1860(attendus=170,ramenes=146.00,corrects=13.00)<br>rappel=0.076precision=0.089f-mesure=0.082 |
| -classe1870(attendus=169,ramenes=103.00,corrects=10.00)<br>rappel=0.059precision=0.097f-mesure=0.074 |
| -classe1880(attendus=169,ramenes=166.00,corrects=20.00)<br>rappel=0.118precision=0.120f-mesure=0.119 |
| -classe1890(attendus=197,ramenes=81.00,corrects=7.00)<br>rappel=0.036precision=0.086f-mesure=0.050 |
| -classe1900(attendus=203,ramenes=153.00,corrects=14.00)<br>rappel=0.069precision=0.092f-mesure=0.079 |
| -classe1910(attendus=201,ramenes=85.00,corrects=11.00)<br>rappel=0.055precision=0.129f-mesure=0.077 |
| -classe1920(attendus=200,ramenes=129.00,corrects=15.00)<br>rappel=0.075precision=0.116f-mesure=0.091 |
| -classe1930(attendus=200,ramenes=96.00,corrects=10.00)<br>rappel=0.050precision=0.104f-mesure=0.068 |
| -classe1940(attendus=198,ramenes=495.00,corrects=82.00)<br>rappel=0.414precision=0.166f-mesure=0.237 |
| -surl’ensembledes15classes<br>macrorappel=0.116macroprecision=0.108macroF-mesure=0.112 | | 1 |
| -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 |
| -classe1820(attendus=169,ramenes=258.00,corrects=29.00)<br>rappel=0.172precision=0.112f-mesure=0.136 |
| -classe1830(attendus=169,ramenes=358.00,corrects=36.00)<br>rappel=0.213precision=0.101f-mesure=0.137 |
| -classe1840(attendus=169,ramenes=86.00,corrects=10.00)<br>rappel=0.059precision=0.116f-mesure=0.078 | | | -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 |
| -classe1820(attendus=169,ramenes=258.00,corrects=29.00)<br>rappel=0.172precision=0.112f-mesure=0.136 |
| -classe1830(attendus=169,ramenes=358.00,corrects=36.00)<br>rappel=0.213precision=0.101f-mesure=0.137 |
| -classe1840(attendus=169,ramenes=86.00,corrects=10.00)<br>rappel=0.059precision=0.116f-mesure=0.078 |
| -classe1850(attendus=169,ramenes=186.00,corrects=16.00)<br>rappel=0.095precision=0.086f-mesure=0.090 |
| -classe1860(attendus=170,ramenes=146.00,corrects=13.00)<br>rappel=0.076precision=0.089f-mesure=0.082 |
| -classe1870(attendus=169,ramenes=103.00,corrects=10.00)<br>rappel=0.059precision=0.097f-mesure=0.074 |
| -classe1880(attendus=169,ramenes=166.00,corrects=20.00)<br>rappel=0.118precision=0.120f-mesure=0.119 |
| -classe1890(attendus=197,ramenes=81.00,corrects=7.00)<br>rappel=0.036precision=0.086f-mesure=0.050 |
| -classe1900(attendus=203,ramenes=153.00,corrects=14.00)<br>rappel=0.069precision=0.092f-mesure=0.079 |
| -classe1910(attendus=201,ramenes=85.00,corrects=11.00)<br>rappel=0.055precision=0.129f-mesure=0.077 |
| -classe1920(attendus=200,ramenes=129.00,corrects=15.00)<br>rappel=0.075precision=0.116f-mesure=0.091 |
| -classe1930(attendus=200,ramenes=96.00,corrects=10.00)<br>rappel=0.050precision=0.104f-mesure=0.068 |
| -classe1940(attendus=198,ramenes=495.00,corrects=82.00)<br>rappel=0.414precision=0.166f-mesure=0.237 |
| -surl’ensembledes15classes<br>macrorappel=0.116macroprecision=0.108macroF-mesure=0.112 | | 0 |
| -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 |
| -classe1820(attendus=169,ramenes=258.00,corrects=29.00)<br>rappel=0.172precision=0.112f-mesure=0.136 |
| -classe1830(attendus=169,ramenes=358.00,corrects=36.00)<br>rappel=0.213precision=0.101f-mesure=0.137 |
| -classe1840(attendus=169,ramenes=86.00,corrects=10.00)<br>rappel=0.059precision=0.116f-mesure=0.078 |
| -classe1850(attendus=169,ramenes=186.00,corrects=16.00)<br>rappel=0.095precision=0.086f-mesure=0.090 |
| -classe1860(attendus=170,ramenes=146.00,corrects=13.00)<br>rappel=0.076precision=0.089f-mesure=0.082 |
| -classe1870(attendus=169,ramenes=103.00,corrects=10.00)<br>rappel=0.059precision=0.097f-mesure=0.074 |
| -classe1880(attendus=169,ramenes=166.00,corrects=20.00)<br>rappel=0.118precision=0.120f-mesure=0.119 | | | -classe1890(attendus=197,ramenes=81.00,corrects=7.00)<br>rappel=0.036precision=0.086f-mesure=0.050 |
| --- |
| -classe1900(attendus=203,ramenes=153.00,corrects=14.00)<br>rappel=0.069precision=0.092f-mesure=0.079 |
| -classe1910(attendus=201,ramenes=85.00,corrects=11.00)<br>rappel=0.055precision=0.129f-mesure=0.077 |
| -classe1920(attendus=200,ramenes=129.00,corrects=15.00)<br>rappel=0.075precision=0.116f-mesure=0.091 |
| -classe1930(attendus=200,ramenes=96.00,corrects=10.00)<br>rappel=0.050precision=0.104f-mesure=0.068 |
| -classe1940(attendus=198,ramenes=495.00,corrects=82.00)<br>rappel=0.414precision=0.166f-mesure=0.237 |
| -surl’ensembledes15classes<br>macrorappel=0.116macroprecision=0.108macroF-mesure=0.112 | | 1 |
| -classe1800(attendus=169,ramenes=127.00,corrects=9.00)<br>rappel=0.053precision=0.071f-mesure=0.061 |
| --- |
| -classe1810(attendus=169,ramenes=252.00,corrects=33.00)<br>rappel=0.195precision=0.131f-mesure=0.157 |
| -classe1820(attendus=169,ramenes=258.00,corrects=29.00)<br>rappel=0.172precision=0.112f-mesure=0.136 |
| -classe1830(attendus=169,ramenes=358.00,corrects=36.00)<br>rappel=0.213precision=0.101f-mesure=0.137 |
| -classe1840(attendus=169,ramenes=86.00,corrects=10.00)<br>rappel=0.059precision=0.116f-mesure=0.078 |
| -classe1850(attendus=169,ramenes=186.00,corrects=16.00)<br>rappel=0.095precision=0.086f-mesure=0.090 |
| -classe1860(attendus=170,ramenes=146.00,corrects=13.00)<br>rappel=0.076precision=0.089f-mesure=0.082 |
| -classe1870(attendus=169,ramenes=103.00,corrects=10.00)<br>rappel=0.059precision=0.097f-mesure=0.074 |
| -classe1880(attendus=169,ramenes=166.00,corrects=20.00)<br>rappel=0.118precision=0.120f-mesure=0.119 | | | -classe1930(attendus=200,ramenes=96.00,corrects=10.00)<br>rappel=0.050precision=0.104f-mesure=0.068 |
| --- |
| -classe1940(attendus=198,ramenes=495.00,corrects=82.00)<br>rappel=0.414precision=0.166f-mesure=0.237 |
| -surl’ensembledes15classes<br>macrorappel=0.116macroprecision=0.108macroF-mesure=0.112 | | 0 |
| 2Dvs2.5Dvs3D | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | |
| | Mean | Std | Mean | Std | Mean | Std | | | 1 | 1485.21,360.41 | 969.35,226.91 | 277.96,142.11 | 183.86,95.31 | 216.13,75.37 | 102.44,49.07 |
| --- | --- | --- | --- | --- | --- | --- |
| 2 | 1448.22,496.99 | 2762.61,896.57 | 255.88,121.53 | 187.85,91.31 | 202.98,75.85 | 86.64,53.21 |
| 3 | 1911.49,412.39 | 3751.34,976.13 | 277.28,103.11 | 214.91,73.48 | 227.99,69.61 | 88.72,54.46 |
| 4 | 1594.86,422.23 | 1204.31,434.19 | 308.21,140.45 | 275.05,96.91 | 247.47,85.41 | 130.01,100.11 |
| 5 | 1435.91,329.55 | 959.59,247.07 | 297.49,130.01 | 227.37,102.01 | 228.55,63.54 | 97.01,46.81 |
| 6 | 1502.01,343.19 | 1031.67,313.21 | 309.82,145.88 | 214.62,82.78 | 255.26,60.56 | 106.99,45.97 |
| 7 | 1834.57,473.37 | 1543.83,804.96 | 333.58,125.07 | 247.67,85.35 | 257.13,67.52 | 112.77,55.22 |
| 8 | 1762.06,536.91 | 3428.56,359.18 | 318.61,245.06 | 199.61,166.53 | 223.06,115.57 | 107.59,83.36 |
| 9 | 5191.66,853.56 | 9109.08,422.23 | 354.45,256.38 | 196.12,175.37 | 291.01,131.62 | 139.48,100.54 |
| 10 | 3241.95,916.71 | 6067.62,355.55 | 325.93,224.51 | 237.14,141.64 | 239.46,111.36 | 113.57,79.05 |
| 11 | 5011.67,503.11 | 8296.25,326.97 | 380.68,223.51 | 263.28,164.91 | 298.28,117.23 | 120.56,105.47 | | 1 |
| 2Dvs2.5Dvs3D | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | |
| | Mean | Std | Mean | Std | Mean | Std | | | 2Dvs2.5Dvs3D | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | |
| | Mean | Std | Mean | Std | Mean | Std |
| 1 | 636.51,335.92 | 458.05,410.72 | 350.38,314.66 | 169.89,210.71 | 178.86,175.18 | 195.45,148.11 |
| 2 | 674.81,164.18 | 483.05,142.16 | 327.13,218.02 | 219.27,174.73 | 173.36,194.73 | 189.16,142.18 |
| 3 | 2227.33,590.95 | 4918.12,1079.51 | 479.55,468.34 | 412.73,281.55 | 468.56,482.34 | 297.08,207.33 |
| 4 | 986.62,824.92 | 1474.53,1737.91 | 324.51,277.44 | 178.71,210.27 | 188.61,167.71 | 192.31,133.46 |
| 5 | 945.29,208.74 | 713.39,376.67 | 875.23,304.89 | 483.12,222.61 | 699.59,195.46 | 445.35,170.75 |
| 6 | 665.61,232.86 | 468.55,366.36 | 461.98,269.71 | 276.23,187.19 | 257.11,200.81 | 209.78,137.04 |
| 7 | 660.83,239.21 | 362.87,184.25 | 519.06,236.97 | 420.72,185.22 | 604.11,173.52 | 296.58,113.85 |
| 8 | 583.52,357.65 | 312.55,245.24 | 458.31,256.74 | 425.81,224.43 | 524.19,245.41 | 308.77,170.46 |
| 9 | 625.89,360.22 | 408.87,216.06 | 463.65,375.31 | 360.06,330.94 | 377.56,304.88 | 261.53,299.25 |
| 10 | 587.73,214.97 | 410.06,487.02 | 440.14,270.42 | 295.54,218.76 | 277.06,203.33 | 252.39,171.86 |
| 11 | 728.69,468.99 | 579.65,628.01 | 490.85,837.33 | 397.51,577.42 | 447.82,571.31 | 299.31,442.53 | | 0 |
| 2Dvs2.5Dvs3D | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | |
| | Mean | Std | Mean | Std | Mean | Std |
| 1 | 1485.21,360.41 | 969.35,226.91 | 277.96,142.11 | 183.86,95.31 | 216.13,75.37 | 102.44,49.07 |
| 2 | 1448.22,496.99 | 2762.61,896.57 | 255.88,121.53 | 187.85,91.31 | 202.98,75.85 | 86.64,53.21 |
| 3 | 1911.49,412.39 | 3751.34,976.13 | 277.28,103.11 | 214.91,73.48 | 227.99,69.61 | 88.72,54.46 |
| 4 | 1594.86,422.23 | 1204.31,434.19 | 308.21,140.45 | 275.05,96.91 | 247.47,85.41 | 130.01,100.11 |
| 5 | 1435.91,329.55 | 959.59,247.07 | 297.49,130.01 | 227.37,102.01 | 228.55,63.54 | 97.01,46.81 |
| 6 | 1502.01,343.19 | 1031.67,313.21 | 309.82,145.88 | 214.62,82.78 | 255.26,60.56 | 106.99,45.97 |
| 7 | 1834.57,473.37 | 1543.83,804.96 | 333.58,125.07 | 247.67,85.35 | 257.13,67.52 | 112.77,55.22 | | | 8 | 1762.06,536.91 | 3428.56,359.18 | 318.61,245.06 | 199.61,166.53 | 223.06,115.57 | 107.59,83.36 |
| --- | --- | --- | --- | --- | --- | --- |
| 9 | 5191.66,853.56 | 9109.08,422.23 | 354.45,256.38 | 196.12,175.37 | 291.01,131.62 | 139.48,100.54 |
| 10 | 3241.95,916.71 | 6067.62,355.55 | 325.93,224.51 | 237.14,141.64 | 239.46,111.36 | 113.57,79.05 |
| 11 | 5011.67,503.11 | 8296.25,326.97 | 380.68,223.51 | 263.28,164.91 | 298.28,117.23 | 120.56,105.47 | | 1 |
| 2Dvs2.5Dvs3D | | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Subject | 2D | 2.5D | 3D | | | |
| | Mean | Std | Mean | Std | Mean | Std |
| 1 | 1485.21,360.41 | 969.35,226.91 | 277.96,142.11 | 183.86,95.31 | 216.13,75.37 | 102.44,49.07 |
| 2 | 1448.22,496.99 | 2762.61,896.57 | 255.88,121.53 | 187.85,91.31 | 202.98,75.85 | 86.64,53.21 |
| 3 | 1911.49,412.39 | 3751.34,976.13 | 277.28,103.11 | 214.91,73.48 | 227.99,69.61 | 88.72,54.46 |
| 4 | 1594.86,422.23 | 1204.31,434.19 | 308.21,140.45 | 275.05,96.91 | 247.47,85.41 | 130.01,100.11 |
| 5 | 1435.91,329.55 | 959.59,247.07 | 297.49,130.01 | 227.37,102.01 | 228.55,63.54 | 97.01,46.81 |
| 6 | 1502.01,343.19 | 1031.67,313.21 | 309.82,145.88 | 214.62,82.78 | 255.26,60.56 | 106.99,45.97 |
| 7 | 1834.57,473.37 | 1543.83,804.96 | 333.58,125.07 | 247.67,85.35 | 257.13,67.52 | 112.77,55.22 | | | 9 | 625.89,360.22 | 408.87,216.06 | 463.65,375.31 | 360.06,330.94 | 377.56,304.88 | 261.53,299.25 |
| --- | --- | --- | --- | --- | --- | --- |
| 10 | 587.73,214.97 | 410.06,487.02 | 440.14,270.42 | 295.54,218.76 | 277.06,203.33 | 252.39,171.86 |
| 11 | 728.69,468.99 | 579.65,628.01 | 490.85,837.33 | 397.51,577.42 | 447.82,571.31 | 299.31,442.53 | | 0 |
| Method | MAEforSAT(ml) | MAEforVAT(ml) |
| --- | --- | --- |
| RANSAC | 12.4995 | 12.5009 | | | Zhaoetal. | 11.1617 | 11.1632 |
| --- | --- | --- |
| GeometricMAD | 13.6875 | 13.6890 |
| AppearanceLoOS | 11.8463 | 11.8473 |
| ContextDrivenFusion | 7.1258 | 7.1281 | | 1 |
| Method | MAEforSAT(ml) | MAEforVAT(ml) |
| --- | --- | --- |
| RANSAC | 12.4995 | 12.5009 | | | Method | MAE | MSE |
| --- | --- | --- |
| HF | 3.51 | 18.70 |
| SPPF | 3.47 | 17.46 |
| LFV | 3.37 | 18.14 |
| ourmethod | 2.41 | 9.12 | | 0 |
| Method | MAEforSAT(ml) | MAEforVAT(ml) |
| --- | --- | --- |
| RANSAC | 12.4995 | 12.5009 | | | Zhaoetal. | 11.1617 | 11.1632 |
| --- | --- | --- |
| GeometricMAD | 13.6875 | 13.6890 |
| AppearanceLoOS | 11.8463 | 11.8473 |
| ContextDrivenFusion | 7.1258 | 7.1281 | | 1 |
| Method | MAEforSAT(ml) | MAEforVAT(ml) |
| --- | --- | --- |
| RANSAC | 12.4995 | 12.5009 | | | SPPF | 3.47 | 17.46 |
| --- | --- | --- |
| LFV | 3.37 | 18.14 |
| ourmethod | 2.41 | 9.12 | | 0 |
| Methods | LFW-funneled4× | LFW-funneled8× | BioID4× | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | PSNR | SSIM | FSIM | PSNR | SSIM | FSIM | PSNR | SSIM | FSIM | PSNR |
| Bicubic | 26.79 | 0.8469 | 0.8947 | 21.92 | 0.6712 | 0.7824 | 25.18 | 0.8170 | 0.8608 | 20.68 | | | SFH | 26.59 | 0.8332 | 0.8917 | 22.12 | 0.6732 | 0.7832 | 25.41 | 0.8034 | 0.8494 | 20.31 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BCCNN | 26.60 | 0.8329 | 0.8982 | 22.62 | 0.6801 | 0.7903 | 24.77 | 0.8034 | 0.8421 | 21.40 |
| MZQ | 25.93 | 0.8313 | 0.8865 | 22.12 | 0.6771 | 0.7802 | 24.66 | 0.8003 | 0.8573 | 21.11 |
| SRCNN | 28.94 | 0.8686 | 0.9069 | 23.92 | 0.6927 | 0.8314 | 27.02 | 0.8517 | 0.8771 | 22.34 |
| VDSR | 29.25 | 0.8711 | 0.9123 | 24.12 | 0.7031 | 0.8391 | 28.52 | 0.8627 | 0.8914 | 24.31 |
| GLN | 30.34 | 0.8922 | 0.9151 | 24.51 | 0.7109 | 0.8405 | 29.13 | 0.8794 | 0.8966 | 24.76 |
| Our | 32.93 | 0.9104 | 0.9427 | 26.17 | 0.7604 | 0.8630 | 31.56 | 0.9002 | 0.9343 | 26.56 | | 1 |
| Methods | LFW-funneled4× | LFW-funneled8× | BioID4× | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | PSNR | SSIM | FSIM | PSNR | SSIM | FSIM | PSNR | SSIM | FSIM | PSNR |
| Bicubic | 26.79 | 0.8469 | 0.8947 | 21.92 | 0.6712 | 0.7824 | 25.18 | 0.8170 | 0.8608 | 20.68 | | | Method | LFW-a4× | LFW-a8× | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| PSNR | SSIM | IFC | WPSNR | NQM | PSNR | SSIM | IFC | WPSNR | NQM | |
| NN | 24.16 | 0.687 | 1.23 | 33.55 | 7.99 | 20.56 | 0.441 | 0.38 | 27.22 | 4.43 |
| Bicubic | 26.62 | 0.796 | 1.84 | 34.61 | 10.72 | 22.16 | 0.575 | 0.77 | 28.38 | 6.13 |
| KK | 27.53 | 0.826 | 2.07 | 36.04 | 11.55 | 22.75 | 0.603 | 0.84 | 29.14 | 6.70 |
| SRCNN | 27.55 | 0.827 | 2.03 | 36.12 | 11.55 | 22.74 | 0.607 | 0.83 | 29.08 | 6.66 |
| LSF | 22.98 | 0.601 | 0.80 | 29.95 | 7.01 | 20.02 | 0.434 | 0.41 | 26.44 | 4.01 |
| MZQ | 26.36 | 0.784 | 1.61 | 34.10 | 10.69 | 22.64 | 0.621 | 0.83 | 29.11 | 6.89 |
| YLY | 25.52 | 0.750 | 1.54 | 33.62 | 9.51 | 20.80 | 0.500 | 0.59 | 27.30 | 4.82 |
| BCCNN | 26.63 | 0.800 | 1.81 | 34.57 | 10.90 | 22.72 | 0.627 | 0.90 | 29.08 | 6.89 |
| GLN | 28.82 | 0.863 | 2.35 | 37.80 | 13.01 | 24.07 | 0.688 | 1.12 | 30.75 | 8.19 | | 0 |
| Methods | LFW-funneled4× | LFW-funneled8× | BioID4× | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | PSNR | SSIM | FSIM | PSNR | SSIM | FSIM | PSNR | SSIM | FSIM | PSNR | | | Bicubic | 26.79 | 0.8469 | 0.8947 | 21.92 | 0.6712 | 0.7824 | 25.18 | 0.8170 | 0.8608 | 20.68 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| SFH | 26.59 | 0.8332 | 0.8917 | 22.12 | 0.6732 | 0.7832 | 25.41 | 0.8034 | 0.8494 | 20.31 |
| BCCNN | 26.60 | 0.8329 | 0.8982 | 22.62 | 0.6801 | 0.7903 | 24.77 | 0.8034 | 0.8421 | 21.40 |
| MZQ | 25.93 | 0.8313 | 0.8865 | 22.12 | 0.6771 | 0.7802 | 24.66 | 0.8003 | 0.8573 | 21.11 |
| SRCNN | 28.94 | 0.8686 | 0.9069 | 23.92 | 0.6927 | 0.8314 | 27.02 | 0.8517 | 0.8771 | 22.34 |
| VDSR | 29.25 | 0.8711 | 0.9123 | 24.12 | 0.7031 | 0.8391 | 28.52 | 0.8627 | 0.8914 | 24.31 |
| GLN | 30.34 | 0.8922 | 0.9151 | 24.51 | 0.7109 | 0.8405 | 29.13 | 0.8794 | 0.8966 | 24.76 |
| Our | 32.93 | 0.9104 | 0.9427 | 26.17 | 0.7604 | 0.8630 | 31.56 | 0.9002 | 0.9343 | 26.56 | | 1 |
| Methods | LFW-funneled4× | LFW-funneled8× | BioID4× | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | PSNR | SSIM | FSIM | PSNR | SSIM | FSIM | PSNR | SSIM | FSIM | PSNR | | | KK | 27.53 | 0.826 | 2.07 | 36.04 | 11.55 | 22.75 | 0.603 | 0.84 | 29.14 | 6.70 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| SRCNN | 27.55 | 0.827 | 2.03 | 36.12 | 11.55 | 22.74 | 0.607 | 0.83 | 29.08 | 6.66 |
| LSF | 22.98 | 0.601 | 0.80 | 29.95 | 7.01 | 20.02 | 0.434 | 0.41 | 26.44 | 4.01 |
| MZQ | 26.36 | 0.784 | 1.61 | 34.10 | 10.69 | 22.64 | 0.621 | 0.83 | 29.11 | 6.89 |
| YLY | 25.52 | 0.750 | 1.54 | 33.62 | 9.51 | 20.80 | 0.500 | 0.59 | 27.30 | 4.82 |
| BCCNN | 26.63 | 0.800 | 1.81 | 34.57 | 10.90 | 22.72 | 0.627 | 0.90 | 29.08 | 6.89 |
| GLN | 28.82 | 0.863 | 2.35 | 37.80 | 13.01 | 24.07 | 0.688 | 1.12 | 30.75 | 8.19 | | 0 |
| song | cc | cc(RG) | avgdist | avgdist(RG) |
| --- | --- | --- | --- | --- |
| B.B.King–Rockmebaby | 0.41 | 0.11 | 2.17 | 3.26 |
| D.Gilmour(PinkFloyd)–Comfortablynumb(1stsolo) | 0.06 | 0.03 | 4.30 | 4.03 | | | E.Clapton(Cream)–Crossroads(2ndsolo) | 0.40 | 0.04 | 3.68 | 4.29 |
| --- | --- | --- | --- | --- |
| J.Hendrix–RedHouse | 0.24 | 0.02 | 3.37 | 5.00 | | 1 |
| song | cc | cc(RG) | avgdist | avgdist(RG) |
| --- | --- | --- | --- | --- |
| B.B.King–Rockmebaby | 0.41 | 0.11 | 2.17 | 3.26 |
| D.Gilmour(PinkFloyd)–Comfortablynumb(1stsolo) | 0.06 | 0.03 | 4.30 | 4.03 | | | track | cc | cc(RG) | L | LRG | σ |
| --- | --- | --- | --- | --- | --- |
| J.Hendrix–RedHouse | 0.24 | 0.02 | 3.37 | 5.00 | 17.8 |
| M.Davis–SoWhat | 0.32 | 0.05 | 2.51 | 4.22 | 10.7 |
| J.Coltrane–GiantSteps | 0.40 | 0.07 | 4.56 | 4.42 | 5.5 |
| N.Paganini–Capriceno.24 | 0.20 | 0.01 | 3.71 | 5.55 | 29.9 |
| N.Rimsky-Korsakov–FlightoftheBumblebee | 0.25 | 0.03 | 2.60 | 4.37 | 14 |
| E.Clapton(Cream)–Crossroads(2ndsolo) | 0.40 | 0.04 | 3.68 | 4.29 | 11.6 |
| B.B.King–WorriedLifeBlues | 0.09 | 0.05 | 3.04 | 3.58 | 2.1 |
| PinkFloyd–Comfortablynumb(1stsolo) | 0.06 | 0.03 | 4.30 | 4.03 | 1.9 | | 0 |
| song | cc | cc(RG) | avgdist | avgdist(RG) |
| --- | --- | --- | --- | --- |
| B.B.King–Rockmebaby | 0.41 | 0.11 | 2.17 | 3.26 | | | D.Gilmour(PinkFloyd)–Comfortablynumb(1stsolo) | 0.06 | 0.03 | 4.30 | 4.03 |
| --- | --- | --- | --- | --- |
| E.Clapton(Cream)–Crossroads(2ndsolo) | 0.40 | 0.04 | 3.68 | 4.29 |
| J.Hendrix–RedHouse | 0.24 | 0.02 | 3.37 | 5.00 | | 1 |
| song | cc | cc(RG) | avgdist | avgdist(RG) |
| --- | --- | --- | --- | --- |
| B.B.King–Rockmebaby | 0.41 | 0.11 | 2.17 | 3.26 | | | N.Paganini–Capriceno.24 | 0.20 | 0.01 | 3.71 | 5.55 | 29.9 |
| --- | --- | --- | --- | --- | --- |
| N.Rimsky-Korsakov–FlightoftheBumblebee | 0.25 | 0.03 | 2.60 | 4.37 | 14 |
| E.Clapton(Cream)–Crossroads(2ndsolo) | 0.40 | 0.04 | 3.68 | 4.29 | 11.6 |
| B.B.King–WorriedLifeBlues | 0.09 | 0.05 | 3.04 | 3.58 | 2.1 |
| PinkFloyd–Comfortablynumb(1stsolo) | 0.06 | 0.03 | 4.30 | 4.03 | 1.9 | | 0 |
| Solver | wcsp-dir | wcsp-log | HT | UP | PP | PWPMS | TT |
| --- | --- | --- | --- | --- | --- | --- | --- |
| WMiFuMax | 6 | 6 | 85 | 100 | 11 | 46 | 0 |
| QWMaxSAT | 14 | 13 | 20 | 0 | 29 | 17 | 8 | | | Sat4j | 3 | 3 | 15 | 37 | 28 | 2 | 8 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| MSUnCore | 14 | 14 | 89 | 100 | 25 | 0 | 0 |
| MaxSatz2013f | 4 | 4 | 0 | 0 | 5 | 25 | 0 |
| WMaxSatz-2009 | 4 | 3 | 0 | 41 | 5 | 12 | 0 |
| WMaxSatz+ | 4 | 3 | 0 | 41 | 5 | 12 | 0 |
| ISAC+ | 17 | 7 | 15 | 100 | 9 | 99 | 9 | | 1 |
| Solver | wcsp-dir | wcsp-log | HT | UP | PP | PWPMS | TT |
| --- | --- | --- | --- | --- | --- | --- | --- |
| WMiFuMax | 6 | 6 | 85 | 100 | 11 | 46 | 0 |
| QWMaxSAT | 14 | 13 | 20 | 0 | 29 | 17 | 8 | | | Solver | auc/paths | auc/sch | csg | planning | warehouses | miplib | rnd-net |
| --- | --- | --- | --- | --- | --- | --- | --- |
| WMiFuMax | 84 | 84 | 5 | 23 | 0 | 1 | 8 |
| QWMaxSAT | 84 | 84 | 10 | 56 | 2 | 4 | 1 |
| Sat4j | 55 | 55 | 10 | 56 | 1 | 4 | 0 |
| MSUnCore | 84 | 84 | 6 | 53 | 0 | 0 | 0 |
| MaxSatz2013f | 81 | 81 | 1 | 41 | 6 | 4 | 1 |
| WMaxSatz-2009 | 67 | 67 | 1 | 45 | 6 | 3 | 0 |
| WMaxSatz+ | 66 | 66 | 1 | 45 | 6 | 2 | 0 |
| ISAC+ | 84 | 84 | 4 | 53 | 18 | 3 | 55 | | 0 |
| Solver | wcsp-dir | wcsp-log | HT | UP | PP | PWPMS | TT |
| --- | --- | --- | --- | --- | --- | --- | --- |
| WMiFuMax | 6 | 6 | 85 | 100 | 11 | 46 | 0 |
| QWMaxSAT | 14 | 13 | 20 | 0 | 29 | 17 | 8 | | | Sat4j | 3 | 3 | 15 | 37 | 28 | 2 | 8 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| MSUnCore | 14 | 14 | 89 | 100 | 25 | 0 | 0 |
| MaxSatz2013f | 4 | 4 | 0 | 0 | 5 | 25 | 0 |
| WMaxSatz-2009 | 4 | 3 | 0 | 41 | 5 | 12 | 0 |
| WMaxSatz+ | 4 | 3 | 0 | 41 | 5 | 12 | 0 |
| ISAC+ | 17 | 7 | 15 | 100 | 9 | 99 | 9 | | 1 |
| Solver | wcsp-dir | wcsp-log | HT | UP | PP | PWPMS | TT |
| --- | --- | --- | --- | --- | --- | --- | --- |
| WMiFuMax | 6 | 6 | 85 | 100 | 11 | 46 | 0 |
| QWMaxSAT | 14 | 13 | 20 | 0 | 29 | 17 | 8 | | | MaxSatz2013f | 81 | 81 | 1 | 41 | 6 | 4 | 1 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| WMaxSatz-2009 | 67 | 67 | 1 | 45 | 6 | 3 | 0 |
| WMaxSatz+ | 66 | 66 | 1 | 45 | 6 | 2 | 0 |
| ISAC+ | 84 | 84 | 4 | 53 | 18 | 3 | 55 | | 0 |
| F-Measure | S1 | S3(ours) | S5(ours) |
| --- | --- | --- | --- |
| MSRC | 0.121 | 0.431 | 0.410 | | | PASCAL | 0.002 | 0.145 | 0.179 |
| --- | --- | --- | --- |
| EDUB | 0.072 | 0.285 | 0.250 |
| Average | 0.065 | 0.287 | 0.280 | | 1 |
| F-Measure | S1 | S3(ours) | S5(ours) |
| --- | --- | --- | --- |
| MSRC | 0.121 | 0.431 | 0.410 | | | χN | fL/C | fC/S3 | fS/S34 | fS/S45 | fODT |
| --- | --- | --- | --- | --- | --- |
| 20 | 0.36797 | 0.25210 | 0.22436 | 0.21461 | 0.20541 |
| 30 | 0.34531 | 0.20048 | 0.16643 | 0.15475 | 0.14434 |
| 40 | 0.33601 | 0.17474 | 0.13631 | 0.12379 | 0.11347 |
| 50 | 0.33120 | 0.15988 | 0.11714 | 0.10418 | 0.09439 |
| 60 | 0.32828 | 0.15059 | 0.10379 | 0.09086 | 0.08086 |
| 70 | 0.32629 | 0.14452 | 0.09387 | 0.08043 | 0.07143 |
| 80 | 0.32482 | 0.14057 | 0.08698 | 0.07143 | 0.06383 |
| 90 | 0.32392 | 0.13737 | 0.08029 | 0.06556 | 0.05789 |
| 100 | 0.32303 | 0.13510 | 0.07535 | 0.05983 | 0.05332 | | 0 |
| F-Measure | S1 | S3(ours) | S5(ours) |
| --- | --- | --- | --- |
| MSRC | 0.121 | 0.431 | 0.410 | | | PASCAL | 0.002 | 0.145 | 0.179 |
| --- | --- | --- | --- |
| EDUB | 0.072 | 0.285 | 0.250 |
| Average | 0.065 | 0.287 | 0.280 | | 1 |
| F-Measure | S1 | S3(ours) | S5(ours) |
| --- | --- | --- | --- |
| MSRC | 0.121 | 0.431 | 0.410 | | | 30 | 0.34531 | 0.20048 | 0.16643 | 0.15475 | 0.14434 |
| --- | --- | --- | --- | --- | --- |
| 40 | 0.33601 | 0.17474 | 0.13631 | 0.12379 | 0.11347 |
| 50 | 0.33120 | 0.15988 | 0.11714 | 0.10418 | 0.09439 |
| 60 | 0.32828 | 0.15059 | 0.10379 | 0.09086 | 0.08086 |
| 70 | 0.32629 | 0.14452 | 0.09387 | 0.08043 | 0.07143 |
| 80 | 0.32482 | 0.14057 | 0.08698 | 0.07143 | 0.06383 |
| 90 | 0.32392 | 0.13737 | 0.08029 | 0.06556 | 0.05789 |
| 100 | 0.32303 | 0.13510 | 0.07535 | 0.05983 | 0.05332 | | 0 |
| Movie | ReleaseDate |
| --- | --- |
| Armored | 2009-12-04 |
| Avatar | 2009-12-18 | | | TheBlindSide | 2009-11-20 |
| --- | --- |
| TheBookofEli | 2010-01-15 |
| Daybreakers | 2010-01-08 |
| DearJohn | 2010-02-05 |
| DidYouHearAboutTheMorgans | 2009-12-18 |
| EdgeOfDarkness | 2010-01-29 |
| ExtraordinaryMeasures | 2010-01-22 |
| FromParisWithLove | 2010-02-05 |
| TheImaginariumofDrParnassus | 2010-01-08 |
| Invictus | 2009-12-11 |
| LeapYear | 2010-01-08 |
| Legion | 2010-01-22 |
| Twilight:NewMoon | 2009-11-20 |
| PirateRadio | 2009-11-13 |
| PrincessAndTheFrog | 2009-12-11 |
| SherlockHolmes | 2009-12-25 |
| SpyNextDoor | 2010-01-15 |
| TheCrazies | 2010-02-26 |
| ToothFairy | 2010-01-22 |
| Transylmania | 2009-12-04 |
| WhenInRome | 2010-01-29 |
| YouthInRevolt | 2010-01-08 | | 1 |
| Movie | ReleaseDate |
| --- | --- |
| Armored | 2009-12-04 |
| Avatar | 2009-12-18 | | | MovieName | NumberofRatings |
| --- | --- |
| StarWars | 583 |
| TommorrowNeverDies | 180 |
| RobinHood:MeninTights | 56 |
| ScreamofStone | 1 | | 0 |
| Movie | ReleaseDate |
| --- | --- |
| Armored | 2009-12-04 |
| Avatar | 2009-12-18 |
| TheBlindSide | 2009-11-20 |
| TheBookofEli | 2010-01-15 |
| Daybreakers | 2010-01-08 |
| DearJohn | 2010-02-05 |
| DidYouHearAboutTheMorgans | 2009-12-18 |
| EdgeOfDarkness | 2010-01-29 |
| ExtraordinaryMeasures | 2010-01-22 |
| FromParisWithLove | 2010-02-05 |
| TheImaginariumofDrParnassus | 2010-01-08 |
| Invictus | 2009-12-11 |
| LeapYear | 2010-01-08 | | | Legion | 2010-01-22 |
| --- | --- |
| Twilight:NewMoon | 2009-11-20 |
| PirateRadio | 2009-11-13 |
| PrincessAndTheFrog | 2009-12-11 |
| SherlockHolmes | 2009-12-25 |
| SpyNextDoor | 2010-01-15 |
| TheCrazies | 2010-02-26 |
| ToothFairy | 2010-01-22 |
| Transylmania | 2009-12-04 |
| WhenInRome | 2010-01-29 |
| YouthInRevolt | 2010-01-08 | | 1 |
| Movie | ReleaseDate |
| --- | --- |
| Armored | 2009-12-04 |
| Avatar | 2009-12-18 |
| TheBlindSide | 2009-11-20 |
| TheBookofEli | 2010-01-15 |
| Daybreakers | 2010-01-08 |
| DearJohn | 2010-02-05 |
| DidYouHearAboutTheMorgans | 2009-12-18 |
| EdgeOfDarkness | 2010-01-29 |
| ExtraordinaryMeasures | 2010-01-22 |
| FromParisWithLove | 2010-02-05 |
| TheImaginariumofDrParnassus | 2010-01-08 |
| Invictus | 2009-12-11 |
| LeapYear | 2010-01-08 | | | RobinHood:MeninTights | 56 |
| --- | --- |
| ScreamofStone | 1 | | 0 |
| Exp | DB | NetA | Ach | NetB | α | β | LR | Momentum |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | db1 | 1 | 1 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 2 | db1 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 3 | db1 | 1 | 3 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 4 | db1 | 1 | 4 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 5 | db1 | 1 | 5 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 6 | db1 | 1 | 6 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 7 | db1 | 1 | 7 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 8 | db1 | 1 | 8 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 9 | db1 | 2 | 1 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 10 | db1 | 2 | 2 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 11 | db1 | 2 | 3 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 12 | db1 | 2 | 4 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 13 | db1 | 2 | 5 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 14 | db1 | 2 | 6 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 15 | db1 | 2 | 7 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 16 | db1 | 2 | 8 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 17 | db1 | NA | NA | B1 | NA | NA | 0.01 | 0.9 | | | 18 | db1a | NA | NA | B1 | NA | NA | 0.01 | 0.9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 19 | db1a | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 20 | db1a | 2 | 2 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 21 | db2 | NA | NA | B1 | NA | NA | 0.01 | 0.9 |
| 22 | db2 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 23 | db3 | NA | NA | B1 | NA | NA | 0.01 | 0.9 |
| 24 | db3 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 25 | db4 | NA | NA | B2 | NA | NA | 0.005 | 0.9 |
| 26 | db4 | NA | NA | B1 | NA | NA | 0.005 | 0.9 |
| 27 | db4 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 28 | db4 | 1 | 2 | B1 | 0.7 | 0.3 | 0.01 | 0.9 |
| 29 | db4 | 2 | 2 | B1 | 0.7 | 0.3 | 0.005 | 0.9 |
| 30 | db4 | 2 | 2 | B1 | 0.3 | 0.7 | 0.005 | 0.9 | | 1 |
| Exp | DB | NetA | Ach | NetB | α | β | LR | Momentum |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | db1 | 1 | 1 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 2 | db1 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 3 | db1 | 1 | 3 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 4 | db1 | 1 | 4 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 5 | db1 | 1 | 5 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 6 | db1 | 1 | 6 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 7 | db1 | 1 | 7 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 8 | db1 | 1 | 8 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 9 | db1 | 2 | 1 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 10 | db1 | 2 | 2 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 11 | db1 | 2 | 3 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 12 | db1 | 2 | 4 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 13 | db1 | 2 | 5 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 14 | db1 | 2 | 6 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 15 | db1 | 2 | 7 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 16 | db1 | 2 | 8 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 17 | db1 | NA | NA | B1 | NA | NA | 0.01 | 0.9 | | | Instance | n | e | d | β(n) | αmin | α/nmin |
| --- | --- | --- | --- | --- | --- | --- |
| L125.ash608 | 125 | 390 | 0.05 | 83 | 2 | 0.016 |
| L125.will199 | 125 | 386 | 0.05 | 83 | 1 | 0.008 |
| L125.west0167 | 125 | 444 | 0.06 | 83 | 1 | 0.008 |
| ash331 | 104 | 331 | 0.06 | 69 | 2 | 0.019 |
| west0132 | 132 | 560 | 0.06 | 88 | 1 | 0.008 |
| rw136 | 136 | 641 | 0.07 | 90 | 1 | 0.007 |
| bcspwr03 | 118 | 576 | 0.08 | 78 | 2 | 0.017 |
| gre115 | 115 | 576 | 0.09 | 76 | 3 | 0.026 |
| L125.dw162 | 125 | 943 | 0.12 | 83 | 6 | 0.048 |
| L125.can187 | 125 | 1022 | 0.13 | 83 | 12 | 0.096 |
| L125.gre185 | 125 | 1177 | 0.15 | 83 | 6 | 0.048 |
| L125.can161 | 125 | 1257 | 0.16 | 83 | 12 | 0.096 |
| L125.lop163 | 125 | 1218 | 0.16 | 83 | 9 | 0.072 |
| can144 | 144 | 1656 | 0.16 | 96 | 18 | 0.125 |
| lunda | 147 | 2837 | 0.26 | 98 | 11 | 0.075 |
| L125.bcsstk05 | 125 | 2701 | 0.35 | 83 | 17 | 0.136 |
| L125.dwt193 | 125 | 2982 | 0.38 | 83 | 21 | 0.168 |
| L125.fs1831 | 125 | 3392 | 0.44 | 83 | 1 | 0.008 |
| bcsstk04 | 132 | 5918 | 0.68 | 88 | 48 | 0.364 |
| arc130 | 130 | 7763 | 0.93 | 86 | 21 | 0.162 | | 0 |
| Exp | DB | NetA | Ach | NetB | α | β | LR | Momentum |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | db1 | 1 | 1 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 2 | db1 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 3 | db1 | 1 | 3 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 4 | db1 | 1 | 4 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 5 | db1 | 1 | 5 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 6 | db1 | 1 | 6 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 7 | db1 | 1 | 7 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 8 | db1 | 1 | 8 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 9 | db1 | 2 | 1 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 10 | db1 | 2 | 2 | B1 | 0.3 | 0.7 | 0.005 | 0.9 | | | 11 | db1 | 2 | 3 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 12 | db1 | 2 | 4 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 13 | db1 | 2 | 5 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 14 | db1 | 2 | 6 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 15 | db1 | 2 | 7 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 16 | db1 | 2 | 8 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 17 | db1 | NA | NA | B1 | NA | NA | 0.01 | 0.9 |
| 18 | db1a | NA | NA | B1 | NA | NA | 0.01 | 0.9 |
| 19 | db1a | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 20 | db1a | 2 | 2 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 21 | db2 | NA | NA | B1 | NA | NA | 0.01 | 0.9 |
| 22 | db2 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 23 | db3 | NA | NA | B1 | NA | NA | 0.01 | 0.9 |
| 24 | db3 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 25 | db4 | NA | NA | B2 | NA | NA | 0.005 | 0.9 |
| 26 | db4 | NA | NA | B1 | NA | NA | 0.005 | 0.9 |
| 27 | db4 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 28 | db4 | 1 | 2 | B1 | 0.7 | 0.3 | 0.01 | 0.9 |
| 29 | db4 | 2 | 2 | B1 | 0.7 | 0.3 | 0.005 | 0.9 |
| 30 | db4 | 2 | 2 | B1 | 0.3 | 0.7 | 0.005 | 0.9 | | 1 |
| Exp | DB | NetA | Ach | NetB | α | β | LR | Momentum |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | db1 | 1 | 1 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 2 | db1 | 1 | 2 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 3 | db1 | 1 | 3 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 4 | db1 | 1 | 4 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 5 | db1 | 1 | 5 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 6 | db1 | 1 | 6 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 7 | db1 | 1 | 7 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 8 | db1 | 1 | 8 | B1 | 0.3 | 0.7 | 0.01 | 0.9 |
| 9 | db1 | 2 | 1 | B1 | 0.3 | 0.7 | 0.005 | 0.9 |
| 10 | db1 | 2 | 2 | B1 | 0.3 | 0.7 | 0.005 | 0.9 | | | L125.dw162 | 125 | 943 | 0.12 | 83 | 6 | 0.048 |
| --- | --- | --- | --- | --- | --- | --- |
| L125.can187 | 125 | 1022 | 0.13 | 83 | 12 | 0.096 |
| L125.gre185 | 125 | 1177 | 0.15 | 83 | 6 | 0.048 |
| L125.can161 | 125 | 1257 | 0.16 | 83 | 12 | 0.096 |
| L125.lop163 | 125 | 1218 | 0.16 | 83 | 9 | 0.072 |
| can144 | 144 | 1656 | 0.16 | 96 | 18 | 0.125 |
| lunda | 147 | 2837 | 0.26 | 98 | 11 | 0.075 |
| L125.bcsstk05 | 125 | 2701 | 0.35 | 83 | 17 | 0.136 |
| L125.dwt193 | 125 | 2982 | 0.38 | 83 | 21 | 0.168 |
| L125.fs1831 | 125 | 3392 | 0.44 | 83 | 1 | 0.008 |
| bcsstk04 | 132 | 5918 | 0.68 | 88 | 48 | 0.364 |
| arc130 | 130 | 7763 | 0.93 | 86 | 21 | 0.162 | | 0 |
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 90.57 | 89.43 | 78.11 | 91.32 | 93.96 | 98.87 | 99.25 | 98.11 | 98.08 |
| 94.3 | 93.3 | 92.0 | 86.42 | 90.07 | 82.01 | 74.81 | 81.75 | 85.48 | | | 92.59 | 90.91 | 83.72 | 91.34 | 89.83 | 92.63 | 94.44 | 84.52 | 90.36 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 91.18 | 89.63 | 85.94 | 82.11 | 81.74 | 85.19 | 85.29 | 88.66 | 90.43 |
| 89.74 | 82.76 | 85.22 | 86.49 | 87.88 | 94.94 | 87.5 | 88.89 | 91.43 |
| 92.08 | 92.08 | 75.25 | 78.22 | 62.63 | 81.82 | 89.69 | 81.44 | 86.46 | | 1 |
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 90.57 | 89.43 | 78.11 | 91.32 | 93.96 | 98.87 | 99.25 | 98.11 | 98.08 |
| 94.3 | 93.3 | 92.0 | 86.42 | 90.07 | 82.01 | 74.81 | 81.75 | 85.48 | | | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 11.16 | 49.67 | 70.23 | 68.07 | 73.86 | 69.33 | 55.63 | 57.75 | 60.18 |
| 91.26 | 89.58 | 82.7 | 83.0 | 83.54 | 88.89 | 84.56 | 86.31 | 84.38 |
| 90.68 | 90.0 | 83.33 | 84.11 | 59.59 | 85.71 | 87.22 | 66.41 | 77.31 |
| 91.3 | 91.21 | 80.0 | 83.53 | 82.28 | 79.73 | 87.32 | 82.61 | 79.69 |
| 93.06 | 91.55 | 92.86 | 84.85 | 90.16 | 85.71 | 80.0 | 86.36 | 88.1 |
| 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 |
| 100.0 | 75.0 | 75.0 | 75.0 | 100.0 | 75.0 | 100.0 | 100.0 | 66.67 |
| 96.3 | 96.3 | 88.46 | 92.0 | 100.0 | 94.74 | 94.74 | 100.0 | 94.74 | | 0 |
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 90.57 | 89.43 | 78.11 | 91.32 | 93.96 | 98.87 | 99.25 | 98.11 | 98.08 |
| 94.3 | 93.3 | 92.0 | 86.42 | 90.07 | 82.01 | 74.81 | 81.75 | 85.48 |
| 92.59 | 90.91 | 83.72 | 91.34 | 89.83 | 92.63 | 94.44 | 84.52 | 90.36 | | | 91.18 | 89.63 | 85.94 | 82.11 | 81.74 | 85.19 | 85.29 | 88.66 | 90.43 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 89.74 | 82.76 | 85.22 | 86.49 | 87.88 | 94.94 | 87.5 | 88.89 | 91.43 |
| 92.08 | 92.08 | 75.25 | 78.22 | 62.63 | 81.82 | 89.69 | 81.44 | 86.46 | | 1 |
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 90.57 | 89.43 | 78.11 | 91.32 | 93.96 | 98.87 | 99.25 | 98.11 | 98.08 |
| 94.3 | 93.3 | 92.0 | 86.42 | 90.07 | 82.01 | 74.81 | 81.75 | 85.48 |
| 92.59 | 90.91 | 83.72 | 91.34 | 89.83 | 92.63 | 94.44 | 84.52 | 90.36 | | | 93.06 | 91.55 | 92.86 | 84.85 | 90.16 | 85.71 | 80.0 | 86.36 | 88.1 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 |
| 100.0 | 75.0 | 75.0 | 75.0 | 100.0 | 75.0 | 100.0 | 100.0 | 66.67 |
| 96.3 | 96.3 | 88.46 | 92.0 | 100.0 | 94.74 | 94.74 | 100.0 | 94.74 | | 0 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.38550.62830.5517<br>0.38890.66610.5673<br>0.68640.76120.5681<br>0.68640.76120.5681<br>0.68640.76120.5681 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.14580.1964-0.0182<br>0.55240.20570.0380<br>0.42630.68270.7261<br>0.42880.68600.7310<br>0.41150.64250.6803 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.41770.81720.8418<br>0.42880.84850.8483<br>0.38110.85030.8137<br>0.39990.80110.8089<br>0.30650.47780.3143<br>0.31910.79390.5243<br>0.32290.74810.5077<br>0.33170.60160.4964 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.58910.44090.2549<br>0.58880.39530.2311<br>0.11870.35460.1308<br>0.10420.36620.1619<br>0.33980.36150.2345<br>0.38640.23030.1368<br>0.44010.28110.1898<br>0.54460.36120.2259 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.23990.47500.2385<br>0.24000.52190.2241<br>-0.08420.14020.0052<br>0.14970.62130.3114<br>0.10940.63570.2575<br>-0.01480.09230.0074<br>0.19750.25790.0639<br>0.08460.47980.2517 | | | k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.57530.57950.2533<br>0.57170.58070.2581<br>0.52930.49440.1180<br>0.54890.51620.1486<br>0.47320.49370.1198<br>0.56920.58000.2550<br>0.56560.56540.2316<br>0.53770.62270.3322 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.54660.82380.7538<br>0.54660.82380.7538<br>0.40150.54680.1140<br>0.37800.54580.1128<br>0.29460.53200.1132<br>0.54660.82380.7538<br>0.54660.82380.7538<br>0.54660.82380.7538 | | 1 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.38550.62830.5517<br>0.38890.66610.5673<br>0.68640.76120.5681<br>0.68640.76120.5681<br>0.68640.76120.5681 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.14580.1964-0.0182<br>0.55240.20570.0380<br>0.42630.68270.7261<br>0.42880.68600.7310<br>0.41150.64250.6803 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.41770.81720.8418<br>0.42880.84850.8483<br>0.38110.85030.8137<br>0.39990.80110.8089<br>0.30650.47780.3143<br>0.31910.79390.5243<br>0.32290.74810.5077<br>0.33170.60160.4964 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.58910.44090.2549<br>0.58880.39530.2311<br>0.11870.35460.1308<br>0.10420.36620.1619<br>0.33980.36150.2345<br>0.38640.23030.1368<br>0.44010.28110.1898<br>0.54460.36120.2259 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.23990.47500.2385<br>0.24000.52190.2241<br>-0.08420.14020.0052<br>0.14970.62130.3114<br>0.10940.63570.2575<br>-0.01480.09230.0074<br>0.19750.25790.0639<br>0.08460.47980.2517 | | | k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.68640.76120.5681<br>0.51710.72060.6906 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.42630.68270.7261<br>0.20220.57240.4363 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.41770.81720.8418<br>0.42880.84850.8483<br>0.38110.85030.8137<br>0.31910.79390.5243<br>0.12580.62290.3602 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.57530.57950.2533<br>0.57170.58070.2581<br>0.52930.49440.1180<br>0.56920.58000.2550<br>0.46860.20630.2675 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.54660.82380.7538<br>0.54660.82380.7538<br>0.40150.54680.1140<br>0.54660.82380.7538<br>0.44630.75290.6966 | | 0 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.38550.62830.5517<br>0.38890.66610.5673<br>0.68640.76120.5681<br>0.68640.76120.5681<br>0.68640.76120.5681 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.14580.1964-0.0182<br>0.55240.20570.0380<br>0.42630.68270.7261<br>0.42880.68600.7310<br>0.41150.64250.6803 | | | k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.41770.81720.8418<br>0.42880.84850.8483<br>0.38110.85030.8137<br>0.39990.80110.8089<br>0.30650.47780.3143<br>0.31910.79390.5243<br>0.32290.74810.5077<br>0.33170.60160.4964 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.58910.44090.2549<br>0.58880.39530.2311<br>0.11870.35460.1308<br>0.10420.36620.1619<br>0.33980.36150.2345<br>0.38640.23030.1368<br>0.44010.28110.1898<br>0.54460.36120.2259 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.23990.47500.2385<br>0.24000.52190.2241<br>-0.08420.14020.0052<br>0.14970.62130.3114<br>0.10940.63570.2575<br>-0.01480.09230.0074<br>0.19750.25790.0639<br>0.08460.47980.2517 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.57530.57950.2533<br>0.57170.58070.2581<br>0.52930.49440.1180<br>0.54890.51620.1486<br>0.47320.49370.1198<br>0.56920.58000.2550<br>0.56560.56540.2316<br>0.53770.62270.3322 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.54660.82380.7538<br>0.54660.82380.7538<br>0.40150.54680.1140<br>0.37800.54580.1128<br>0.29460.53200.1132<br>0.54660.82380.7538<br>0.54660.82380.7538<br>0.54660.82380.7538 | | 1 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.38550.62830.5517<br>0.38890.66610.5673<br>0.68640.76120.5681<br>0.68640.76120.5681<br>0.68640.76120.5681 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.14580.1964-0.0182<br>0.55240.20570.0380<br>0.42630.68270.7261<br>0.42880.68600.7310<br>0.41150.64250.6803 | | | k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.57530.57950.2533<br>0.57170.58070.2581<br>0.52930.49440.1180<br>0.56920.58000.2550<br>0.46860.20630.2675 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.54660.82380.7538<br>0.54660.82380.7538<br>0.40150.54680.1140<br>0.54660.82380.7538<br>0.44630.75290.6966 | | 0 |
| a | 1000111010010011000010000011010111000101101100 |
| --- | --- |
| a | 1110111110010100011101001001100001000001101011 | | | a | 1111011111001010001110100100110000100000110101 |
| --- | --- |
| a1 | 0100101101100111101111100101000111010010011000 |
| 0<br>a | 1111011111001010001110100100110000100000110101 |
| a | 1000101101100111101111100101000111010010011000 |
| a | 1100010110110011110111110010100011101001001100 |
| a | 0100000110101110001011011001111011111001010001 | | 1 |
| a | 1000111010010011000010000011010111000101101100 |
| --- | --- |
| a | 1110111110010100011101001001100001000001101011 | | | GLK<br>0.815 | 0000000001011111000000000101111100000000010111110000000001011111<br>0000000001011111111111110101111100000000010111111111111101011111 |
| --- | --- |
| Das<br>0.823 | 0000000000101111000000110101111100000000000111111100111100011111<br>0000000000101111111111000101111100000000000111111111111100011111 |
| Davis<br>0.818 | 0000011100000000000001111111111100001111000000000000111111111111<br>0000111100000000000001111111111100001111001100010000111111111111 |
| ABK<br>0.824 | 0000010100000000010101010000010100000101000000000101010100000101<br>0101010111111111010101011111111101010101111111110101010111111111 |
| Coe1<br>0.851 | 0000000100010100001100001101011100010001000011110011100101010111<br>0000010110110100111111110001011111110001001111011111100101010111 |
| Coe2<br>0.860 | 0001010001010001001100000101110000000000010100001100111001011111<br>0001011100010001111111110101111100001111010100111100111101011111 | | 0 |
| a | 1000111010010011000010000011010111000101101100 |
| --- | --- |
| a | 1110111110010100011101001001100001000001101011 |
| a | 1111011111001010001110100100110000100000110101 |
| a1 | 0100101101100111101111100101000111010010011000 | | | 0<br>a | 1111011111001010001110100100110000100000110101 |
| --- | --- |
| a | 1000101101100111101111100101000111010010011000 |
| a | 1100010110110011110111110010100011101001001100 |
| a | 0100000110101110001011011001111011111001010001 | | 1 |
| a | 1000111010010011000010000011010111000101101100 |
| --- | --- |
| a | 1110111110010100011101001001100001000001101011 |
| a | 1111011111001010001110100100110000100000110101 |
| a1 | 0100101101100111101111100101000111010010011000 | | | Davis<br>0.818 | 0000011100000000000001111111111100001111000000000000111111111111<br>0000111100000000000001111111111100001111001100010000111111111111 |
| --- | --- |
| ABK<br>0.824 | 0000010100000000010101010000010100000101000000000101010100000101<br>0101010111111111010101011111111101010101111111110101010111111111 |
| Coe1<br>0.851 | 0000000100010100001100001101011100010001000011110011100101010111<br>0000010110110100111111110001011111110001001111011111100101010111 |
| Coe2<br>0.860 | 0001010001010001001100000101110000000000010100001100111001011111<br>0001011100010001111111110101111100001111010100111100111101011111 | | 0 |
| Episode<br>expiry | Freq.<br>Th. | Time<br>(sec) | Size<br>(No.) | Patterns<br>Discovered |
| --- | --- | --- | --- | --- |
| 0.001 | 0.01 | 0.28 | 3(1) | ABC:614 |
| 0.002 | 0.01 | 0.25 | 3(1) | ABC:617 | | | 0.004 | 0.01 | 0.28 | 4(1) | ABCD:537 |
| --- | --- | --- | --- | --- |
| 0.006 | 0.01 | 0.32 | 4(2) | XABC:602<br>ABCD:542 | | 1 |
| Episode<br>expiry | Freq.<br>Th. | Time<br>(sec) | Size<br>(No.) | Patterns<br>Discovered |
| --- | --- | --- | --- | --- |
| 0.001 | 0.01 | 0.28 | 3(1) | ABC:614 |
| 0.002 | 0.01 | 0.25 | 3(1) | ABC:617 | | | | Episode | Action |
| --- | --- | --- |
| 1-200 | 543.1 | 543.4 |
| 201-2,000 | 194.0 | 195.6 |
| 2,001-17,000 | 63.0 | 69.3 |
| 17,001-20,000 | 46.3 | 54.6 | | 0 |
| Episode<br>expiry | Freq.<br>Th. | Time<br>(sec) | Size<br>(No.) | Patterns<br>Discovered |
| --- | --- | --- | --- | --- |
| 0.001 | 0.01 | 0.28 | 3(1) | ABC:614 |
| 0.002 | 0.01 | 0.25 | 3(1) | ABC:617 | | | 0.004 | 0.01 | 0.28 | 4(1) | ABCD:537 |
| --- | --- | --- | --- | --- |
| 0.006 | 0.01 | 0.32 | 4(2) | XABC:602<br>ABCD:542 | | 1 |
| Episode<br>expiry | Freq.<br>Th. | Time<br>(sec) | Size<br>(No.) | Patterns<br>Discovered |
| --- | --- | --- | --- | --- |
| 0.001 | 0.01 | 0.28 | 3(1) | ABC:614 |
| 0.002 | 0.01 | 0.25 | 3(1) | ABC:617 | | | 2,001-17,000 | 63.0 | 69.3 |
| --- | --- | --- |
| 17,001-20,000 | 46.3 | 54.6 | | 0 |
| PASCALVOC<br>(20classes) | ClosestILSVRC-DETclass<br>(200classestotal) | Averageobjectscale | RCNNAP |
| --- | --- | --- | --- |
| PASCAL | ILSVRC | PASCAL | ILSVRC |
| aeroplane | airplane | 0.28 | 0.47 |
| bicycle | bicycle | 0.29 | 0.46 |
| bird | bird | | |
| boat | watercraft | | |
| bottle | winebottle(orwaterbottle) | | |
| bus | bus | | |
| car | car | | |
| cat | domesticcat | | |
| chair | chair | | |
| cow | cattle | | |
| diningtable | table | | | | | dog | dog |
| --- | --- |
| horse | horse |
| motorbike | motorcyle |
| person | person |
| pottedplant | flowerpot |
| sheep | sheep |
| sofa | sofa |
| train | train |
| tv/monitor | tvormonitor | | 1 |
| PASCALVOC<br>(20classes) | ClosestILSVRC-DETclass<br>(200classestotal) | Averageobjectscale | RCNNAP |
| --- | --- | --- | --- |
| PASCAL | ILSVRC | PASCAL | ILSVRC |
| aeroplane | airplane | 0.28 | 0.47 |
| bicycle | bicycle | 0.29 | 0.46 |
| bird | bird | | |
| boat | watercraft | | |
| bottle | winebottle(orwaterbottle) | | |
| bus | bus | | |
| car | car | | |
| cat | domesticcat | | |
| chair | chair | | |
| cow | cattle | | |
| diningtable | table | | | | | PASCALVOC | COCO |
| --- | --- |
| aeroplane | airplane |
| bike | bicycle |
| bird | bird |
| boat | boat |
| bottle | bottle |
| bus | bus |
| car | car |
| cat | cat |
| chair | chair |
| cow | cow |
| diningtable | diningtable |
| dog | dog |
| horse | horse |
| motorbike | motorcycle |
| person | person |
| pottedplant | pottedplant |
| sheep | sheep |
| sofa | couch |
| train | train |
| tv | tv | | 0 |
| PASCALVOC<br>(20classes) | ClosestILSVRC-DETclass<br>(200classestotal) | Averageobjectscale | RCNNAP |
| --- | --- | --- | --- |
| PASCAL | ILSVRC | PASCAL | ILSVRC |
| aeroplane | airplane | 0.28 | 0.47 |
| bicycle | bicycle | 0.29 | 0.46 |
| bird | bird | | |
| boat | watercraft | | |
| bottle | winebottle(orwaterbottle) | | |
| bus | bus | | |
| car | car | | |
| cat | domesticcat | | |
| chair | chair | | |
| cow | cattle | | |
| diningtable | table | | |
| dog | dog | | |
| horse | horse | | | | | motorbike | motorcyle |
| --- | --- |
| person | person |
| pottedplant | flowerpot |
| sheep | sheep |
| sofa | sofa |
| train | train |
| tv/monitor | tvormonitor | | 1 |
| PASCALVOC<br>(20classes) | ClosestILSVRC-DETclass<br>(200classestotal) | Averageobjectscale | RCNNAP |
| --- | --- | --- | --- |
| PASCAL | ILSVRC | PASCAL | ILSVRC |
| aeroplane | airplane | 0.28 | 0.47 |
| bicycle | bicycle | 0.29 | 0.46 |
| bird | bird | | |
| boat | watercraft | | |
| bottle | winebottle(orwaterbottle) | | |
| bus | bus | | |
| car | car | | |
| cat | domesticcat | | |
| chair | chair | | |
| cow | cattle | | |
| diningtable | table | | |
| dog | dog | | |
| horse | horse | | | | | chair | chair |
| --- | --- |
| cow | cow |
| diningtable | diningtable |
| dog | dog |
| horse | horse |
| motorbike | motorcycle |
| person | person |
| pottedplant | pottedplant |
| sheep | sheep |
| sofa | couch |
| train | train |
| tv | tv | | 0 |
| VideoSequences | Biswasetal. | Proposed |
| --- | --- | --- |
| Sequence1 | 4.96 | 0.20 |
| Sequence2 | 5.08 | 0.31 |
| Sequence3 | 4.66 | 0.23 | | | Sequence4 | 4.49 | 0.33 |
| --- | --- | --- |
| Sequence5 | 4.32 | 0.08 |
| Sequence6 | 5.32 | 0.31 |
| Sequence7 | 4.95 | 0.38 | | 1 |
| VideoSequences | Biswasetal. | Proposed |
| --- | --- | --- |
| Sequence1 | 4.96 | 0.20 |
| Sequence2 | 5.08 | 0.31 |
| Sequence3 | 4.66 | 0.23 | | | TestSequences | Alietal. | Biswasetal. | Proposed |
| --- | --- | --- | --- |
| Sequence1 | 0.63 | 0.60 | 0.90 |
| Sequence2 | 0.28 | 0.67 | 0.66 |
| Sequence3 | 0.57 | 0.74 | 0.75 |
| Sequence4 | 0.67 | 0.68 | 0.68 |
| Sequence5 | 0.78 | 0.24 | 0.46 |
| Sequence6 | 0.41 | 0.62 | 0.81 |
| Sequence7 | 0.60 | 0.15 | 0.53 | | 0 |
| VideoSequences | Biswasetal. | Proposed |
| --- | --- | --- |
| Sequence1 | 4.96 | 0.20 | | | Sequence2 | 5.08 | 0.31 |
| --- | --- | --- |
| Sequence3 | 4.66 | 0.23 |
| Sequence4 | 4.49 | 0.33 |
| Sequence5 | 4.32 | 0.08 |
| Sequence6 | 5.32 | 0.31 |
| Sequence7 | 4.95 | 0.38 | | 1 |
| VideoSequences | Biswasetal. | Proposed |
| --- | --- | --- |
| Sequence1 | 4.96 | 0.20 | | | Sequence3 | 0.57 | 0.74 | 0.75 |
| --- | --- | --- | --- |
| Sequence4 | 0.67 | 0.68 | 0.68 |
| Sequence5 | 0.78 | 0.24 | 0.46 |
| Sequence6 | 0.41 | 0.62 | 0.81 |
| Sequence7 | 0.60 | 0.15 | 0.53 | | 0 |
| CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.7944 | | | | | | | | FS.cont | 0.7941 | −0.0003 | 0.0846 | 83 | 3 | 0.0662 |
| --- | --- | --- | --- | --- | --- | --- |
| TOM.cont | 0.8034 | 0.0089 | 0.0636 | 105 | 2 | 0.1782 |
| HC.cont | 0.8266 | 0.0281 | 0.2244 | 109 | 34 | 0.1199 |
| Original.binary | 0.7847 | −0.0097 | 0.0502 | 48 | 1 | 0.2222 |
| Jaccard | 0.7291 | −0.0653 | 0.2738 | 28 | 18 | 0.4759 |
| Pvalue | 0.6374 | −0.1570 | 0.1740 | 5 | 3 | 0.5691 |
| FS.binary | 0.6750 | −0.1195 | 0.1740 | 5 | 1 | 0.4945 |
| TOM.binary | 0.7365 | −0.0579 | 0.3332 | 23 | 9 | 0.3227 |
| HC.binary | 0.7578 | −0.0367 | 0.2989 | 35 | 25 | 0.3773 | | 1 |
| CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.7944 | | | | | | | | CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.784 | | | | | |
| FS.cont | 0.7364 | -0.0476 | 0.013 | 5 | 0 | 0.1968 |
| TOM.cont | 0.7617 | -0.0223 | 0.024 | 16 | 0 | 0.1495 |
| HC.cont | 0.7932 | 0.0092 | 0.115 | 60 | 8 | 0.0456 |
| Original.binary | 0.7884 | 0.0044 | 0.1648 | 60 | 2 | 0.0458 |
| Jaccard | 0.7244 | -0.0596 | 0.0697 | 10 | 2 | 0.2298 |
| Pvalue | 0.5765 | -0.2075 | -0.037 | 0 | 0 | 0.4829 |
| FS.binary | 0.6396 | -0.1444 | -0.0285 | 0 | 0 | 0.3161 |
| TOM.binary | 0.7713 | -0.0127 | 0.1076 | 27 | 1 | 0.1495 |
| HC.binary | 0.7808 | -0.0032 | 0.1294 | 43 | 6 | 0.0827 | | 0 |
| CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.7944 | | | | | | | | FS.cont | 0.7941 | −0.0003 | 0.0846 | 83 | 3 | 0.0662 |
| --- | --- | --- | --- | --- | --- | --- |
| TOM.cont | 0.8034 | 0.0089 | 0.0636 | 105 | 2 | 0.1782 |
| HC.cont | 0.8266 | 0.0281 | 0.2244 | 109 | 34 | 0.1199 |
| Original.binary | 0.7847 | −0.0097 | 0.0502 | 48 | 1 | 0.2222 |
| Jaccard | 0.7291 | −0.0653 | 0.2738 | 28 | 18 | 0.4759 |
| Pvalue | 0.6374 | −0.1570 | 0.1740 | 5 | 3 | 0.5691 |
| FS.binary | 0.6750 | −0.1195 | 0.1740 | 5 | 1 | 0.4945 |
| TOM.binary | 0.7365 | −0.0579 | 0.3332 | 23 | 9 | 0.3227 |
| HC.binary | 0.7578 | −0.0367 | 0.2989 | 35 | 25 | 0.3773 | | 1 |
| CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.7944 | | | | | | | | FS.cont | 0.7364 | -0.0476 | 0.013 | 5 | 0 | 0.1968 |
| --- | --- | --- | --- | --- | --- | --- |
| TOM.cont | 0.7617 | -0.0223 | 0.024 | 16 | 0 | 0.1495 |
| HC.cont | 0.7932 | 0.0092 | 0.115 | 60 | 8 | 0.0456 |
| Original.binary | 0.7884 | 0.0044 | 0.1648 | 60 | 2 | 0.0458 |
| Jaccard | 0.7244 | -0.0596 | 0.0697 | 10 | 2 | 0.2298 |
| Pvalue | 0.5765 | -0.2075 | -0.037 | 0 | 0 | 0.4829 |
| FS.binary | 0.6396 | -0.1444 | -0.0285 | 0 | 0 | 0.3161 |
| TOM.binary | 0.7713 | -0.0127 | 0.1076 | 27 | 1 | 0.1495 |
| HC.binary | 0.7808 | -0.0032 | 0.1294 | 43 | 6 | 0.0827 | | 0 |
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