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 ⌀ |
|---|---|---|---|---|---|
3D Interacting Hand Pose Estimation | InterHand2.6M | DIGIT | https://arxiv.org/abs/2107.00434v2 | MPJPE Test | 14.27 |
3D Interacting Hand Pose Estimation | InterHand2.6M | DIGIT | https://arxiv.org/abs/2107.00434v2 | MRRPE Test | 29.22 |
3D Interacting Hand Pose Estimation | InterHand2.6M | DIGIT | https://arxiv.org/abs/2107.00434v2 | MPVPE Test | - |
3D Interacting Hand Pose Estimation | InterHand2.6M | InterNet | https://arxiv.org/abs/2008.09309v1 | MPJPE Test | 16.01 |
3D Interacting Hand Pose Estimation | InterHand2.6M | InterNet | https://arxiv.org/abs/2008.09309v1 | MRRPE Test | 32.60 |
3D Interacting Hand Pose Estimation | InterHand2.6M | InterNet | https://arxiv.org/abs/2008.09309v1 | MPVPE Test | - |
MMR total | MRR-Benchmark | Claude 3.5 Sonnet | https://www-cdn.anthropic.com/fed9cc193a14b84131812372d8d5857f8f304c52/Model_Card_Claude_3_Addendum.pdf | Total Column Score | 463 |
MMR total | MRR-Benchmark | GPT-4o | https://arxiv.org/abs/2406.09781v1 | Total Column Score | 457 |
MMR total | MRR-Benchmark | GPT-4V | https://arxiv.org/abs/2309.17421v2 | Total Column Score | 415 |
MMR total | MRR-Benchmark | LLaVA-NEXT-34B | https://arxiv.org/abs/2304.08485v2 | Total Column Score | 412 |
MMR total | MRR-Benchmark | Phi-3-Vision | https://arxiv.org/abs/2404.14219v4 | Total Column Score | 397 |
MMR total | MRR-Benchmark | InternVL2-8B | https://arxiv.org/abs/2312.14238v3 | Total Column Score | 368 |
MMR total | MRR-Benchmark | Qwen-vl-max | https://arxiv.org/abs/2308.12966v3 | Total Column Score | 366 |
MMR total | MRR-Benchmark | LLaVA-NEXT-13B | https://arxiv.org/abs/2304.08485v2 | Total Column Score | 335 |
MMR total | MRR-Benchmark | Qwen-vl-plus | https://arxiv.org/abs/2308.12966v3 | Total Column Score | 310 |
MMR total | MRR-Benchmark | Idefics-2-8B | https://arxiv.org/abs/2405.02246v1 | Total Column Score | 256 |
MMR total | MRR-Benchmark | LLaVA-1.5-13B | https://arxiv.org/abs/2304.08485v2 | Total Column Score | 243 |
MMR total | MRR-Benchmark | InternVL2-1B | https://arxiv.org/abs/2312.14238v3 | Total Column Score | 237 |
MMR total | MRR-Benchmark | Monkey-Chat-7B | https://arxiv.org/abs/2311.06607v4 | Total Column Score | 214 |
MMR total | MRR-Benchmark | Idefics-80B | https://arxiv.org/abs/2306.16527v2 | Total Column Score | 139 |
Audio Quality Assessment | ODAQ: Open Dataset of Audio Quality | NMR | https://github.com/Fraunhofer-IIS/ODAQ/tree/main/benchmark | Pearson correlation coefficient (PCC) | 0.89 |
Audio Quality Assessment | ODAQ: Open Dataset of Audio Quality | PEAQ-CSM | https://github.com/Fraunhofer-IIS/ODAQ/tree/main/benchmark | Pearson correlation coefficient (PCC) | 0.89 |
Audio Quality Assessment | ODAQ: Open Dataset of Audio Quality | 2f-model | https://github.com/Fraunhofer-IIS/ODAQ/tree/main/benchmark | Pearson correlation coefficient (PCC) | 0.87 |
Audio Quality Assessment | ODAQ: Open Dataset of Audio Quality | PEAQ (ODG) | https://github.com/Fraunhofer-IIS/ODAQ/tree/main/benchmark | Pearson correlation coefficient (PCC) | 0.87 |
Audio Quality Assessment | ODAQ: Open Dataset of Audio Quality | ViSQOLAudioV3 | https://github.com/Fraunhofer-IIS/ODAQ/tree/main/benchmark | Pearson correlation coefficient (PCC) | 0.77 |
Audio Quality Assessment | ODAQ: Open Dataset of Audio Quality | SMAQ | https://github.com/Fraunhofer-IIS/ODAQ/tree/main/benchmark | Pearson correlation coefficient (PCC) | 0.77 |
Audio Quality Assessment | ODAQ: Open Dataset of Audio Quality | PESQ | https://github.com/Fraunhofer-IIS/ODAQ/tree/main/benchmark | Pearson correlation coefficient (PCC) | 0.74 |
Audio Quality Assessment | ODAQ: Open Dataset of Audio Quality | SI-SDR | https://github.com/Fraunhofer-IIS/ODAQ/tree/main/benchmark | Pearson correlation coefficient (PCC) | 0.44 |
Audio Quality Assessment | ODAQ: Open Dataset of Audio Quality | DNSMOS (OVRL) | https://github.com/Fraunhofer-IIS/ODAQ/tree/main/benchmark | Pearson correlation coefficient (PCC) | 0.38 |
Sound Source Localization | ^(#$!@#$)(()))****** | YOLO | https://arxiv.org/abs/2103.03954v2 | 0..5sec | 21 |
Natural Language Queries | Ego4D | EgoVideo | https://arxiv.org/abs/2406.18070v4 | R@1 IoU=0.3 | 28.05 |
Natural Language Queries | Ego4D | EgoVideo | https://arxiv.org/abs/2406.18070v4 | R@5 IoU=0.3 | 44.16 |
Natural Language Queries | Ego4D | EgoVideo | https://arxiv.org/abs/2406.18070v4 | R@1 IoU=0.5 | 19.31 |
Natural Language Queries | Ego4D | EgoVideo | https://arxiv.org/abs/2406.18070v4 | R@5 IoU=0.5 | 31.37 |
Natural Language Queries | Ego4D | EgoVideo | https://arxiv.org/abs/2406.18070v4 | R@1 Mean(0.3 and 0.5) | 23.68 |
Natural Language Queries | Ego4D | DeCafNet-100% | https://arxiv.org/abs/2505.16376v1 | R@1 IoU=0.3 | 22.21 |
Natural Language Queries | Ego4D | DeCafNet-100% | https://arxiv.org/abs/2505.16376v1 | R@5 IoU=0.3 | 45.63 |
Natural Language Queries | Ego4D | DeCafNet-100% | https://arxiv.org/abs/2505.16376v1 | R@1 IoU=0.5 | 15.52 |
Natural Language Queries | Ego4D | DeCafNet-100% | https://arxiv.org/abs/2505.16376v1 | R@5 IoU=0.5 | 33.93 |
Natural Language Queries | Ego4D | DeCafNet-100% | https://arxiv.org/abs/2505.16376v1 | R@1 Mean(0.3 and 0.5) | 18.86 |
Natural Language Queries | Ego4D | DeCafNet-50% | https://arxiv.org/abs/2505.16376v1 | R@1 IoU=0.3 | 20.81 |
Natural Language Queries | Ego4D | DeCafNet-50% | https://arxiv.org/abs/2505.16376v1 | R@5 IoU=0.3 | 42.40 |
Natural Language Queries | Ego4D | DeCafNet-50% | https://arxiv.org/abs/2505.16376v1 | R@1 IoU=0.5 | 15.04 |
Natural Language Queries | Ego4D | DeCafNet-50% | https://arxiv.org/abs/2505.16376v1 | R@5 IoU=0.5 | 31.68 |
Natural Language Queries | Ego4D | DeCafNet-50% | https://arxiv.org/abs/2505.16376v1 | R@1 Mean(0.3 and 0.5) | 17.93 |
Natural Language Queries | Ego4D | RGNet | https://arxiv.org/abs/2312.06729v3 | R@1 IoU=0.3 | 20.63 |
Natural Language Queries | Ego4D | RGNet | https://arxiv.org/abs/2312.06729v3 | R@5 IoU=0.3 | 41.67 |
Natural Language Queries | Ego4D | RGNet | https://arxiv.org/abs/2312.06729v3 | R@1 IoU=0.5 | 12.47 |
Natural Language Queries | Ego4D | RGNet | https://arxiv.org/abs/2312.06729v3 | R@5 IoU=0.5 | 25.08 |
Natural Language Queries | Ego4D | RGNet | https://arxiv.org/abs/2312.06729v3 | R@1 Mean(0.3 and 0.5) | 16.55 |
Natural Language Queries | Ego4D | DeCafNet-50% (no NaQ) | https://arxiv.org/abs/2505.16376v1 | R@1 IoU=0.3 | 18.10 |
Natural Language Queries | Ego4D | DeCafNet-50% (no NaQ) | https://arxiv.org/abs/2505.16376v1 | R@5 IoU=0.3 | 38.85 |
Natural Language Queries | Ego4D | DeCafNet-50% (no NaQ) | https://arxiv.org/abs/2505.16376v1 | R@1 IoU=0.5 | 12.55 |
Natural Language Queries | Ego4D | DeCafNet-50% (no NaQ) | https://arxiv.org/abs/2505.16376v1 | R@5 IoU=0.5 | 28.27 |
Natural Language Queries | Ego4D | DeCafNet-50% (no NaQ) | https://arxiv.org/abs/2505.16376v1 | R@1 Mean(0.3 and 0.5) | 15.32 |
Natural Language Queries | Ego4D | InternVideo | https://arxiv.org/abs/2211.09529v1 | R@1 IoU=0.3 | 16.45 |
Natural Language Queries | Ego4D | InternVideo | https://arxiv.org/abs/2211.09529v1 | R@5 IoU=0.3 | 22.95 |
Natural Language Queries | Ego4D | InternVideo | https://arxiv.org/abs/2211.09529v1 | R@1 IoU=0.5 | 10.06 |
Natural Language Queries | Ego4D | InternVideo | https://arxiv.org/abs/2211.09529v1 | R@5 IoU=0.5 | 16.10 |
Natural Language Queries | Ego4D | InternVideo | https://arxiv.org/abs/2211.09529v1 | R@1 Mean(0.3 and 0.5) | 13.26 |
Natural Language Queries | Ego4D | UniMD+Sync. | https://arxiv.org/abs/2404.04933v2 | R@1 IoU=0.3 | 14.16 |
Natural Language Queries | Ego4D | UniMD+Sync. | https://arxiv.org/abs/2404.04933v2 | R@5 IoU=0.3 | 26.95 |
Natural Language Queries | Ego4D | UniMD+Sync. | https://arxiv.org/abs/2404.04933v2 | R@1 IoU=0.5 | 10.06 |
Natural Language Queries | Ego4D | UniMD+Sync. | https://arxiv.org/abs/2404.04933v2 | R@5 IoU=0.5 | 19.16 |
Natural Language Queries | Ego4D | UniMD+Sync. | https://arxiv.org/abs/2404.04933v2 | R@1 Mean(0.3 and 0.5) | 12.11 |
Natural Language Queries | Ego4D | ReLER@ZJU-Alibaba | https://arxiv.org/abs/2207.00383v2 | R@1 IoU=0.3 | 12.89 |
Natural Language Queries | Ego4D | ReLER@ZJU-Alibaba | https://arxiv.org/abs/2207.00383v2 | R@5 IoU=0.3 | 15.41 |
Natural Language Queries | Ego4D | ReLER@ZJU-Alibaba | https://arxiv.org/abs/2207.00383v2 | R@1 IoU=0.5 | 8.14 |
Natural Language Queries | Ego4D | ReLER@ZJU-Alibaba | https://arxiv.org/abs/2207.00383v2 | R@5 IoU=0.5 | 9.94 |
Natural Language Queries | Ego4D | ReLER@ZJU-Alibaba | https://arxiv.org/abs/2207.00383v2 | R@1 Mean(0.3 and 0.5) | 10.52 |
Natural Language Queries | Ego4D | EgoVLP | https://arxiv.org/abs/2206.01670v2 | R@1 IoU=0.3 | 10.46 |
Natural Language Queries | Ego4D | EgoVLP | https://arxiv.org/abs/2206.01670v2 | R@5 IoU=0.3 | 16.76 |
Natural Language Queries | Ego4D | EgoVLP | https://arxiv.org/abs/2206.01670v2 | R@1 IoU=0.5 | 6.24 |
Natural Language Queries | Ego4D | EgoVLP | https://arxiv.org/abs/2206.01670v2 | R@5 IoU=0.5 | 11.29 |
Natural Language Queries | Ego4D | EgoVLP | https://arxiv.org/abs/2206.01670v2 | R@1 Mean(0.3 and 0.5) | 8.35 |
Natural Language Queries | Ego4D | EgoVLPv2 | https://arxiv.org/abs/2307.05463v2 | R@1 IoU=0.3 | 12.95 |
Natural Language Queries | Ego4D | EgoVLPv2 | https://arxiv.org/abs/2307.05463v2 | R@5 IoU=0.3 | 23.80 |
Natural Language Queries | Ego4D | EgoVLPv2 | https://arxiv.org/abs/2307.05463v2 | R@1 IoU=0.5 | 7.91 |
Natural Language Queries | Ego4D | EgoVLPv2 | https://arxiv.org/abs/2307.05463v2 | R@5 IoU=0.5 | 16.11 |
Lifelike 3D Human Generation | THuman2.0 Dataset | Human-VDM | https://arxiv.org/abs/2409.02851v1 | CLIP Similarity | 0.9235 |
Lifelike 3D Human Generation | THuman2.0 Dataset | Human-VDM | https://arxiv.org/abs/2409.02851v1 | SSIM | 0.9228 |
Lifelike 3D Human Generation | THuman2.0 Dataset | Human-VDM | https://arxiv.org/abs/2409.02851v1 | LPIPS | 0.0957 |
Lifelike 3D Human Generation | THuman2.0 Dataset | Human-VDM | https://arxiv.org/abs/2409.02851v1 | PSNR | 20.068 |
Lifelike 3D Human Generation | THuman2.0 Dataset | Ultraman | https://arxiv.org/abs/2403.12028v1 | CLIP Similarity | 0.9131 |
Lifelike 3D Human Generation | THuman2.0 Dataset | Ultraman | https://arxiv.org/abs/2403.12028v1 | SSIM | 0.8958 |
Lifelike 3D Human Generation | THuman2.0 Dataset | Ultraman | https://arxiv.org/abs/2403.12028v1 | LPIPS | 0.1338 |
Lifelike 3D Human Generation | THuman2.0 Dataset | Ultraman | https://arxiv.org/abs/2403.12028v1 | PSNR | 17.4877 |
Lifelike 3D Human Generation | THuman2.0 Dataset | SiTH | https://arxiv.org/abs/2311.15855v2 | CLIP Similarity | 0.8978 |
Lifelike 3D Human Generation | THuman2.0 Dataset | SiTH | https://arxiv.org/abs/2311.15855v2 | SSIM | 0.8963 |
Lifelike 3D Human Generation | THuman2.0 Dataset | SiTH | https://arxiv.org/abs/2311.15855v2 | LPIPS | 0.1396 |
Lifelike 3D Human Generation | THuman2.0 Dataset | SiTH | https://arxiv.org/abs/2311.15855v2 | PSNR | 17.0533 |
Lifelike 3D Human Generation | THuman2.0 Dataset | PaMIR | https://arxiv.org/abs/2007.03858v2 | CLIP Similarity | 0.8861 |
Lifelike 3D Human Generation | THuman2.0 Dataset | PaMIR | https://arxiv.org/abs/2007.03858v2 | SSIM | 0.8924 |
Lifelike 3D Human Generation | THuman2.0 Dataset | PaMIR | https://arxiv.org/abs/2007.03858v2 | LPIPS | 0.1461 |
Lifelike 3D Human Generation | THuman2.0 Dataset | PaMIR | https://arxiv.org/abs/2007.03858v2 | PSNR | 16.6267 |
Lifelike 3D Human Generation | THuman2.0 Dataset | SIFU | https://arxiv.org/abs/2312.06704v3 | CLIP Similarity | 0.8663 |
Lifelike 3D Human Generation | THuman2.0 Dataset | SIFU | https://arxiv.org/abs/2312.06704v3 | SSIM | 0.7931 |
Lifelike 3D Human Generation | THuman2.0 Dataset | SIFU | https://arxiv.org/abs/2312.06704v3 | LPIPS | 0.1500 |
Lifelike 3D Human Generation | THuman2.0 Dataset | SIFU | https://arxiv.org/abs/2312.06704v3 | PSNR | 16.4600 |
Lifelike 3D Human Generation | THuman2.0 Dataset | PIFu | https://arxiv.org/abs/1905.05172v3 | CLIP Similarity | 0.8501 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.