task_path stringlengths 3 199 ⌀ | dataset stringlengths 1 128 ⌀ | model_name stringlengths 1 223 ⌀ | paper_url stringlengths 21 601 ⌀ | metric_name stringlengths 1 50 ⌀ | metric_value stringlengths 1 9.22k ⌀ |
|---|---|---|---|---|---|
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI | Ego-Net | https://arxiv.org/abs/2011.08464v5 | Average Orientation Similarity | 89.43 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | Ego-Net (Monocular RGB only) | https://arxiv.org/abs/2011.08464v5 | Average Orientation Similarity | 80.96 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | Deep-Manta | http://arxiv.org/abs/1703.07570v1 | Average Orientation Similarity | 80.39 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | 3D R-CNN | http://openaccess.thecvf.com/content_cvpr_2018/html/Kundu_3D-RCNN_Instance-Level_3D_CVPR_2018_paper.html | Average Orientation Similarity | 80.07 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | SubCNN | http://arxiv.org/abs/1604.04693v3 | Average Orientation Similarity | 78.68 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | DSGN (Stereo) | https://arxiv.org/abs/2001.03398v3 | Average Orientation Similarity | 78.27 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | RTM-3D | https://arxiv.org/abs/2001.03343v1 | Average Orientation Similarity | 77.18 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | FQNet | https://arxiv.org/abs/1904.12681v2 | Average Orientation Similarity | 76.85 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | Mono3D | http://openaccess.thecvf.com/content_cvpr_2016/html/Chen_Monocular_3D_Object_CVPR_2016_paper.html | Average Orientation Similarity | 76.84 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | Deep3DBoX | http://arxiv.org/abs/1612.00496v2 | Average Orientation Similarity | 76.76 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | 3DOP | http://papers.nips.cc/paper/5644-3d-object-proposals-for-accurate-object-class-detection | Average Orientation Similarity | 76.52 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | MonoPair | https://arxiv.org/abs/2003.00504v1 | Average Orientation Similarity | 76.45 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | ML-Fusion | http://openaccess.thecvf.com/content_cvpr_2018/html/Xu_Multi-Level_Fusion_Based_CVPR_2018_paper.html | Average Orientation Similarity | 76.37 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | MonoPSR | http://arxiv.org/abs/1904.01690v1 | Average Orientation Similarity | 72.26 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | Disp-RCNN (Stereo) | https://arxiv.org/abs/2004.03572v1 | Average Orientation Similarity | 67.16 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | M3D-RPN | https://arxiv.org/abs/1907.06038v2 | Average Orientation Similarity | 67.08 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | RAR-Net | https://arxiv.org/abs/2008.13748v1 | Average Orientation Similarity | 66.90 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | D4LCN | https://arxiv.org/abs/1912.04799v2 | Average Orientation Similarity | 63.98 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | GS3D | http://arxiv.org/abs/1903.10955v2 | Average Orientation Similarity | 61.85 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | KITTI Cars Hard | Kinematic3D | https://arxiv.org/abs/2007.09548v1 | Average Orientation Similarity | 34.81 |
1 Image, 2*2 Stitchi > Pose Estimation > Vehicle Pose Estimation | CarFusion | Occlusion-NET | http://openaccess.thecvf.com/content_CVPR_2019/html/Reddy_Occlusion-Net_2D3D_Occluded_Keypoint_Localization_Using_Graph_Networks_CVPR_2019_paper.html | PCK | 88.8 |
1 Image, 2*2 Stitchi > Pose Estimation > Car Pose Estimation | ApolloCar3D | Zauss et al. | https://arxiv.org/abs/2110.00988v1 | Detection Rate | 91.9 |
1 Image, 2*2 Stitchi > Pose Estimation > Car Pose Estimation | ApolloCar3D | OpenPifPaf | https://arxiv.org/abs/2103.02440v2 | Detection Rate | 86.1 |
1 Image, 2*2 Stitchi > Pose Estimation > Car Pose Estimation | ApolloCar3D | CPM | http://arxiv.org/abs/1602.00134v4 | Detection Rate | 75.4 |
1 Image, 2*2 Stitchi > Pose Estimation > RF-based Pose Estimation | RF-MMD | HCN | http://arxiv.org/abs/1804.06055v1 | mAP (@0.1, Through-wall) | 78.5 |
1 Image, 2*2 Stitchi > Pose Estimation > RF-based Pose Estimation | RF-MMD | HCN | http://arxiv.org/abs/1804.06055v1 | mAP (@0.1, Visible) | 82,5 |
1 Image, 2*2 Stitchi > Pose Estimation > RF-based Pose Estimation | RF-MMD | Aryokee | https://doi.org/10.1145/3264947 | mAP (@0.1, Through-wall) | 72.9 |
1 Image, 2*2 Stitchi > Pose Estimation > RF-based Pose Estimation | RF-MMD | Aryokee | https://doi.org/10.1145/3264947 | mAP (@0.1, Visible) | 78.3 |
1 Image, 2*2 Stitchi > Pose Estimation > RF-based Pose Estimation | RF-MMD | RF-Action | https://arxiv.org/abs/1909.09300v1 | mAP (@0.1, Visible) | 90.1 |
1 Image, 2*2 Stitchi > Pose Estimation > RF-based Pose Estimation | RF-MMD | RF-Action | https://arxiv.org/abs/1909.09300v1 | mAP (@0.1, Through-wall) | 86.5 |
1 Image, 2*2 Stitchi > Pose Estimation > Activeness Detection | COCO test-dev | Lightweight OpenPose | https://arxiv.org/abs/2010.13714v1 | Accuracy (%) | 76.67 |
1 Image, 2*2 Stitchi > Style Transfer | StyleBench | StyleShot | https://arxiv.org/abs/2407.01414v1 | CLIP Score | 0.660 |
1 Image, 2*2 Stitchi > Style Transfer | StyleBench | StyleID | https://arxiv.org/abs/2312.09008v2 | CLIP Score | 0.604 |
1 Image, 2*2 Stitchi > Style Transfer | StyleBench | StrTR-2 | http://openaccess.thecvf.com//content/CVPR2022/html/Deng_StyTr2_Image_Style_Transfer_With_Transformers_CVPR_2022_paper.html | CLIP Score | 0.586 |
1 Image, 2*2 Stitchi > Style Transfer | StyleBench | CAST | https://arxiv.org/abs/2205.09542v2 | CLIP Score | 0.575 |
1 Image, 2*2 Stitchi > Style Transfer | StyleBench | AdaAttN | https://arxiv.org/abs/2108.03647v2 | CLIP Score | 0.569 |
1 Image, 2*2 Stitchi > Style Transfer | StyleBench | InST | https://arxiv.org/abs/2211.13203v3 | CLIP Score | 0.569 |
1 Image, 2*2 Stitchi > Style Transfer | StyleBench | EFDM | https://arxiv.org/abs/2203.07740v2 | CLIP Score | 0.561 |
1 Image, 2*2 Stitchi > Style Transfer | 01/01/1967' AND 2*3*8=6*8 AND 'AncJ'='AncJ | Ali | https://arxiv.org/abs/2402.04499v2 | 0..5sec | Download |
1 Image, 2*2 Stitchi > Style Transfer | GYAFC | BART (TextBox 2.0) | https://arxiv.org/abs/2212.13005v1 | BLEU-4 | 76.93 |
1 Image, 2*2 Stitchi > Style Transfer | GYAFC | BART (TextBox 2.0) | https://arxiv.org/abs/2212.13005v1 | Accuracy | 94.37 |
1 Image, 2*2 Stitchi > Style Transfer | GYAFC | BART (TextBox 2.0) | https://arxiv.org/abs/2212.13005v1 | Harmonic mean | 84.74 |
1 Image, 2*2 Stitchi > Style Transfer | ^(#$!@#$)(()))****** | studio Ghibli | https://arxiv.org/abs/2206.09379v2 | 0..5sec | studio Ghibli |
1 Image, 2*2 Stitchi > Style Transfer | WikiArt | StyleFlow-Content-Fixed-I2I | https://arxiv.org/abs/2207.01909v1 | SSIM | 0.45 |
1 Image, 2*2 Stitchi > Style Transfer | WikiArt | Mamba-ST | https://arxiv.org/abs/2409.10385v1 | ArtFID | 27.11 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | RAT-Diffusion | https://arxiv.org/abs/2410.01638v1 | FID | 5.00 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Re-Imagen (Finetuned) | https://arxiv.org/abs/2209.14491v3 | FID | 5.25 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | U-ViT-S/2-Deep | https://arxiv.org/abs/2209.12152v4 | FID | 5.48 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | GLIGEN (fine-tuned, Detection + Caption data) | https://arxiv.org/abs/2301.07093v2 | FID | 5.61 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | GLIGEN (fine-tuned, Detection data only) | https://arxiv.org/abs/2301.07093v2 | FID | 5.82 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | U-ViT-S/2 | https://arxiv.org/abs/2209.12152v4 | FID | 5.95 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | ConPreDiff | https://arxiv.org/abs/2401.02015v1 | FID | 6.21 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | ConPreDiff | https://arxiv.org/abs/2401.02015v1 | Zero shot FID | 6.21 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | TLDM | https://arxiv.org/abs/2202.09671v4 | FID | 6.29 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | GLIGEN (fine-tuned, Grounding data) | https://arxiv.org/abs/2301.07093v2 | FID | 6.38 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | RAPHAEL (zero-shot) | https://arxiv.org/abs/2305.18295v5 | FID | 6.61 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | ERNIE-ViLG 2.0 (zero-shot) | https://arxiv.org/abs/2210.15257v2 | FID | 6.75 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Re-Imagen | https://arxiv.org/abs/2209.14491v3 | FID | 6.88 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | eDiff-I (zero-shot) | https://arxiv.org/abs/2211.01324v5 | FID | 6.95 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Swinv2-Imagen | https://arxiv.org/abs/2210.09549v1 | FID | 7.21 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Swinv2-Imagen | https://arxiv.org/abs/2210.09549v1 | Inception score | 31.46 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Imagen (zero-shot) | https://arxiv.org/abs/2205.11487v1 | FID | 7.27 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | GigaGAN (Zero-shot, 64x64) | https://arxiv.org/abs/2303.05511v2 | FID | 7.28 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | StyleGAN-T (Zero-shot, 64x64) | https://arxiv.org/abs/2301.09515v1 | FID | 7.3 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Make-a-Scene (unfiltered) | https://arxiv.org/abs/2203.13131v1 | FID | 7.55 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Kandinsky | https://arxiv.org/abs/2310.03502v1 | FID | 8.03 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Lafite | https://arxiv.org/abs/2111.13792v3 | FID | 8.12 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Lafite | https://arxiv.org/abs/2111.13792v3 | Inception score | 32.34 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Lafite | https://arxiv.org/abs/2111.13792v3 | SOA-C | 61.09 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | SiD-LSG (Data-free distillation, zero-shot FID) | https://arxiv.org/abs/2406.01561v3 | FID | 8.15 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | SiD-LSG (Data-free distillation, zero-shot FID) | https://arxiv.org/abs/2406.01561v3 | Zero shot FID | 8.15 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | simple diffusion (U-ViT) | https://arxiv.org/abs/2301.11093v2 | FID | 8.3 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | GigaGAN (Zero-shot, 256x256) | https://arxiv.org/abs/2303.05511v2 | FID | 9.09 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | XMC-GAN (256 x 256) | https://arxiv.org/abs/2111.12417v1 | FID | 9.3 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | XMC-GAN (256 x 256) | https://arxiv.org/abs/2111.12417v1 | Inception score | 30.5 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | XMC-GAN | https://arxiv.org/abs/2101.04702v5 | FID | 9.33 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | DALL-E 2 | https://arxiv.org/abs/2204.06125v1 | FID | 10.39 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Corgi-Semi | https://arxiv.org/abs/2211.15388v2 | FID | 10.6 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Corgi | https://arxiv.org/abs/2211.15388v2 | FID | 10.88 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | TR0N (StyleGAN-XL, LAION2BCLIP, BLIP-2, zero-shot) | https://arxiv.org/abs/2304.13742v1 | FID | 10.9 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Make-a-Scene (unfiltered) | https://arxiv.org/abs/2203.13131v1 | FID | 11.84 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | GLIDE (zero-shot) | https://arxiv.org/abs/2112.10741v3 | FID | 12.24 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | KNN-Diffusion | https://arxiv.org/abs/2204.02849v2 | FID | 12.5 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | GALIP (CC12m) | https://arxiv.org/abs/2301.12959v1 | FID | 12.54 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Latent Diffusion (LDM-KL-8-G) | https://arxiv.org/abs/2112.10752v2 | FID | 12.63 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | Stable Diffusion | https://arxiv.org/abs/2211.12561v2 | FID | 12.63 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | NÜWA (256 x 256) | https://arxiv.org/abs/2111.12417v1 | FID | 12.9 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | NÜWA (256 x 256) | https://arxiv.org/abs/2111.12417v1 | Inception score | 27.2 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | VQ-Diffusion-F | https://arxiv.org/abs/2111.14822v3 | FID | 13.86 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | StyleGAN-T (Zero-shot, 256x256) | https://arxiv.org/abs/2301.09515v1 | FID | 13.9 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | RAT-GAN | https://arxiv.org/abs/2204.10482v1 | FID | 14.6 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | ERNIE-ViLG | https://arxiv.org/abs/2112.15283v1 | FID | 14.7 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | RA-CM3 (2.7B) | https://arxiv.org/abs/2211.12561v2 | FID | 15.7 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | CogView2(6B, Finetuned) | https://arxiv.org/abs/2204.14217v2 | FID | 17.7 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | VQ-Diffusion-B | https://arxiv.org/abs/2111.14822v3 | FID | 19.75 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | DM-GAN+CL | https://arxiv.org/abs/2107.02423v2 | FID | 20.79 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | DM-GAN+CL | https://arxiv.org/abs/2107.02423v2 | Inception score | 33.34 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | FuseDream (few-shot, k=5) | https://arxiv.org/abs/2112.01573v1 | FID | 21.16 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | FuseDream (few-shot, k=5) | https://arxiv.org/abs/2112.01573v1 | Inception score | 34.26 |
1 Image, 2*2 Stitchi > Text-to-Image Generation | COCO (Common Objects in Context) | FuseDream (k=5, 256) | https://arxiv.org/abs/2112.01573v1 | FID | 21.16 |
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