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 ⌀ |
|---|---|---|---|---|---|
Age Estimation | mebeblurf | POE | https://arxiv.org/abs/2103.13629v1 | Accuracy | 60.5 |
Age Estimation | mebeblurf | SORD | http://openaccess.thecvf.com/content_CVPR_2019/html/Diaz_Soft_Labels_for_Ordinal_Regression_CVPR_2019_paper.html | MAE | 0.49 |
Age Estimation | mebeblurf | SORD | http://openaccess.thecvf.com/content_CVPR_2019/html/Diaz_Soft_Labels_for_Ordinal_Regression_CVPR_2019_paper.html | Accuracy | 59.6 |
Age Estimation | mebeblurf | GP-DNNOR | http://openaccess.thecvf.com/content_ICCV_2019/html/Liu_Probabilistic_Deep_Ordinal_Regression_Based_on_Gaussian_Processes_ICCV_2019_paper.html | MAE | 0.54 |
Age Estimation | mebeblurf | GP-DNNOR | http://openaccess.thecvf.com/content_ICCV_2019/html/Liu_Probabilistic_Deep_Ordinal_Regression_Based_on_Gaussian_Processes_ICCV_2019_paper.html | Accuracy | 57.4 |
Age Estimation | mebeblurf | CNNPOR | http://openaccess.thecvf.com/content_cvpr_2018/html/Liu_A_Constrained_Deep_CVPR_2018_paper.html | MAE | 0.55 |
Age Estimation | mebeblurf | CNNPOR | http://openaccess.thecvf.com/content_cvpr_2018/html/Liu_A_Constrained_Deep_CVPR_2018_paper.html | Accuracy | 57.4 |
Age Estimation | UTKFace | MiVOLO-D1 | https://arxiv.org/abs/2307.04616v2 | MAE | 3.7 |
Age Estimation | UTKFace | FaRL+MLP | https://arxiv.org/abs/2307.04570v3 | MAE | 3.87 |
Age Estimation | UTKFace | VOLO-D1 age&gender | https://arxiv.org/abs/2307.04616v2 | MAE | 4.23 |
Age Estimation | UTKFace | ResNet-50-SORD | https://arxiv.org/abs/2307.04570v3 | MAE | 4.36 |
Age Estimation | UTKFace | MWR | https://arxiv.org/abs/2203.13122v1 | MAE | 4.37 |
Age Estimation | UTKFace | ResNet-50-Cross-Entropy | https://arxiv.org/abs/2307.04570v3 | MAE | 4.38 |
Age Estimation | UTKFace | ResNet-50-DLDL | https://arxiv.org/abs/2307.04570v3 | MAE | 4.39 |
Age Estimation | UTKFace | ResNet-50-OR-CNN | https://arxiv.org/abs/2307.04570v3 | MAE | 4.40 |
Age Estimation | UTKFace | ResNet-50-DLDL-v2 | https://arxiv.org/abs/2307.04570v3 | MAE | 4.42 |
Age Estimation | UTKFace | ResNet-50-Mean-Variance | https://arxiv.org/abs/2307.04570v3 | MAE | 4.42 |
Age Estimation | UTKFace | ResNet-50-Unimodal-Concentrated | https://arxiv.org/abs/2307.04570v3 | MAE | 4.47 |
Age Estimation | UTKFace | Randomized Bins | https://arxiv.org/abs/2006.15864v1 | MAE | 4.55 |
Age Estimation | UTKFace | ResNet-50-Regression | https://arxiv.org/abs/2307.04570v3 | MAE | 4.72 |
Age Estimation | UTKFace | CORAL | https://arxiv.org/abs/1901.07884v7 | MAE | 5.39 |
Age Estimation | KANFace | FP-Age | https://arxiv.org/abs/2106.11145v2 | Average mean absolute error | 6.81 |
Age Estimation | FGNET | MWR | https://arxiv.org/abs/2203.13122v1 | MAE | 2.23 |
Age Estimation | FGNET | BridgeNet | http://arxiv.org/abs/1904.03358v1 | MAE | 2.56 |
Age Estimation | FGNET | C3AE (WIKI-IMDB) | http://arxiv.org/abs/1904.05059v2 | MAE | 2.95 |
Age Estimation | FGNET | DEX | https://link.springer.com/article/10.1007/s11263-016-0940-3 | MAE | 3.09 |
Age Estimation | FGNET | CMAAE-OR | http://arxiv.org/abs/1804.02740v1 | MAE | 3.62 |
Age Estimation | FGNET | DRFs | http://arxiv.org/abs/1712.07195v1 | MAE | 3.85 |
Age Estimation | FGNET | Zhu et al. (Actual) | http://arxiv.org/abs/1804.02740v1 | MAE | 4.58 |
Age Estimation | FGNET | AEBFI | http://arxiv.org/abs/1904.05059v2 | MAE | 52 |
Age Estimation | MORPH | CMAAE-OR | http://arxiv.org/abs/1804.02740v1 | MAE | 1.48 |
Age Estimation | CACD | MiVOLO-V2 | https://arxiv.org/abs/2403.02302v4 | MAE | 3.89 |
Age Estimation | CACD | ResNet-50-Cross-Entropy | https://arxiv.org/abs/2307.04570v3 | MAE | 3.96 |
Age Estimation | CACD | ResNet-50-DLDL | https://arxiv.org/abs/2307.04570v3 | MAE | 3.96 |
Age Estimation | CACD | ResNet-50-DLDL-v2 | https://arxiv.org/abs/2307.04570v3 | MAE | 3.96 |
Age Estimation | CACD | ResNet-50-SORD | https://arxiv.org/abs/2307.04570v3 | MAE | 3.96 |
Age Estimation | CACD | FaRL+MLP | https://arxiv.org/abs/2307.04570v3 | MAE | 3.96 |
Age Estimation | CACD | ResNet-50-OR-CNN | https://arxiv.org/abs/2307.04570v3 | MAE | 4.01 |
Age Estimation | CACD | ResNet-50-Regression | https://arxiv.org/abs/2307.04570v3 | MAE | 4.06 |
Age Estimation | CACD | ResNet-50-Mean-Variance | https://arxiv.org/abs/2307.04570v3 | MAE | 4.07 |
Age Estimation | CACD | ResNet-50-Unimodal-Concentrated | https://arxiv.org/abs/2307.04570v3 | MAE | 4.10 |
Age Estimation | CACD | MWR | https://arxiv.org/abs/2203.13122v1 | MAE | 4.41 |
Age Estimation | CACD | RNDF | https://arxiv.org/abs/1908.10737v1 | MAE | 4.60 |
Age Estimation | CACD | CORAL | https://arxiv.org/abs/1901.07884v7 | MAE | 5.35 |
Age Estimation | MORPH Album2 | Hierarchical Attention-based Age Estimation (RS) | https://arxiv.org/abs/2103.09882v2 | MAE | 1.13 |
Age Estimation | MORPH Album2 | MataAge | https://arxiv.org/abs/2207.05288v1 | MAE | 1.81 |
Age Estimation | MORPH Album2 | DLDL-v2 (ThinAgeNet) | https://arxiv.org/abs/2007.01771v2 | MAE | 1.969 |
Age Estimation | MORPH Album2 | MWR | https://arxiv.org/abs/2203.13122v1 | MAE | 2.00 |
Age Estimation | MORPH Album2 | MWR | https://arxiv.org/abs/2203.13122v1 | CS | 95.0 |
Age Estimation | MORPH Album2 | DLDL+VGG-Face | http://arxiv.org/abs/1611.01731v2 | MAE | 2.42±0.01 |
Age Estimation | MORPH Album2 | DLDL+VGG-Face (KL, Max)3 | http://arxiv.org/abs/1611.01731v2 | MAE | 2.42 |
Age Estimation | MORPH Album2 | MegaAge (w. IMDB-WIKI) | http://arxiv.org/abs/1708.09687v2 | MAE | 2.52 |
Age Estimation | MORPH Album2 | Hierarchical Attention-based Age Estimation (SE) | https://arxiv.org/abs/2103.09882v2 | MAE | 2.53 |
Age Estimation | MORPH Album2 | CORAL | https://arxiv.org/abs/1901.07884v7 | MAE | 2.59 |
Age Estimation | MORPH Album2 (SE) | ResNet-50-Unimodal-Concentrated | https://arxiv.org/abs/2307.04570v3 | MAE | 2.78 |
Age Estimation | MORPH Album2 (SE) | ResNet-50-Cross-Entropy | https://arxiv.org/abs/2307.04570v3 | MAE | 2.81 |
Age Estimation | MORPH Album2 (SE) | ResNet-50-DLDL | https://arxiv.org/abs/2307.04570v3 | MAE | 2.81 |
Age Estimation | MORPH Album2 (SE) | ResNet-50-SORD | https://arxiv.org/abs/2307.04570v3 | MAE | 2.81 |
Age Estimation | MORPH Album2 (SE) | ResNet-50-DLDL-v2 | https://arxiv.org/abs/2307.04570v3 | MAE | 2.82 |
Age Estimation | MORPH Album2 (SE) | ResNet-50-OR-CNN | https://arxiv.org/abs/2307.04570v3 | MAE | 2.83 |
Age Estimation | MORPH Album2 (SE) | ResNet-50-Mean-Variance | https://arxiv.org/abs/2307.04570v3 | MAE | 2.83 |
Age Estimation | MORPH Album2 (SE) | ResNet-50-Regression | https://arxiv.org/abs/2307.04570v3 | MAE | 2.83 |
Age Estimation | MORPH Album2 (SE) | FaRL+MLP | https://arxiv.org/abs/2307.04570v3 | MAE | 3.04 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | OrdinalCLIP | https://arxiv.org/abs/2206.02338v2 | MAE | 4.94 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | OrdinalCLIP | https://arxiv.org/abs/2206.02338v2 | MAE (2 shot) | 4.36 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | OrdinalCLIP | https://arxiv.org/abs/2206.02338v2 | MAE (4 shot) | 3.55 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | OrdinalCLIP | https://arxiv.org/abs/2206.02338v2 | MAE (8 shot) | 3.31 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | OrdinalCLIP | https://arxiv.org/abs/2206.02338v2 | MAE (16 shot) | 3.07 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | CoOp | https://arxiv.org/abs/2109.01134v6 | MAE | 5.09 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | CoOp | https://arxiv.org/abs/2109.01134v6 | MAE (2 shot) | 4.50 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | CoOp | https://arxiv.org/abs/2109.01134v6 | MAE (4 shot) | 3.81 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | CoOp | https://arxiv.org/abs/2109.01134v6 | MAE (8 shot) | 3.57 |
Age Estimation > Few-shot Age Estimation | MORPH Album2 | CoOp | https://arxiv.org/abs/2109.01134v6 | MAE (16 shot) | 3.23 |
Multimodal Reasoning | AlgoPuzzleVQA | GPT-4 | https://arxiv.org/abs/2403.03864v3 | Acc | 30.3 |
Multimodal Reasoning | MATH-V | GPT4V | https://arxiv.org/abs/2402.14804v1 | Accuracy | 22.76 |
Multimodal Reasoning | MATH-V | Gemini Pro | https://arxiv.org/abs/2402.14804v1 | Accuracy | 17.66 |
Multimodal Reasoning | MATH-V | Qwen-VL-Max | https://arxiv.org/abs/2402.14804v1 | Accuracy | 15.59 |
Multimodal Reasoning | MATH-V | InternLM-XComposer2-VL | https://arxiv.org/abs/2402.14804v1 | Accuracy | 14.54 |
Multimodal Reasoning | REBUS | GPT-4V | https://arxiv.org/abs/2401.05604v2 | Accuracy | 24.0 |
Multimodal Reasoning | REBUS | Gemini Pro | https://arxiv.org/abs/2401.05604v2 | Accuracy | 13.2 |
Multimodal Reasoning | REBUS | LLaVa-1.5-13B | https://arxiv.org/abs/2401.05604v2 | Accuracy | 1.8 |
Multimodal Reasoning | REBUS | LLaVa-1.5-7B | https://arxiv.org/abs/2401.05604v2 | Accuracy | 1.5 |
Multimodal Reasoning | REBUS | BLIP2-FLAN-T5-XXL | https://arxiv.org/abs/2401.05604v2 | Accuracy | 0.9 |
Multimodal Reasoning | REBUS | CogVLM | https://arxiv.org/abs/2401.05604v2 | Accuracy | 0.9 |
Multimodal Reasoning | REBUS | QWEN | https://arxiv.org/abs/2401.05604v2 | Accuracy | 0.9 |
Multimodal Reasoning | REBUS | InstructBLIP | https://arxiv.org/abs/2401.05604v2 | Accuracy | 0.6 |
Panoptic Segmentation | Panoptic nuScenes test | (AF)2-S3Net + CenterPoint | https://arxiv.org/abs/2109.03805v3 | PQ | 76.8 |
Panoptic Segmentation | Panoptic nuScenes test | (AF)2-S3Net + CenterPoint | https://arxiv.org/abs/2109.03805v3 | SQ | 89.5 |
Panoptic Segmentation | Panoptic nuScenes test | (AF)2-S3Net + CenterPoint | https://arxiv.org/abs/2109.03805v3 | RQ | 85.4 |
Panoptic Segmentation | Panoptic nuScenes test | (AF)2-S3Net + CenterPoint | https://arxiv.org/abs/2109.03805v3 | mIoU | 78.8 |
Panoptic Segmentation | ScanNet | OneFormer3D | https://arxiv.org/abs/2311.14405v1 | PQ | 71.2 |
Panoptic Segmentation | ScanNet | OneFormer3D | https://arxiv.org/abs/2311.14405v1 | PQ_th | 69.6 |
Panoptic Segmentation | ScanNet | OneFormer3D | https://arxiv.org/abs/2311.14405v1 | PQ_st | 86.1 |
Panoptic Segmentation | ScanNet | SuperCluster | https://arxiv.org/abs/2401.06704v2 | PQ | 58.7 |
Panoptic Segmentation | ScanNet | SuperCluster | https://arxiv.org/abs/2401.06704v2 | PQ_th | 69.1 |
Panoptic Segmentation | ScanNet | SuperCluster | https://arxiv.org/abs/2401.06704v2 | PQ_st | 84.1 |
Panoptic Segmentation | ScanNet | PanopticFusion | https://arxiv.org/abs/1903.01177v2 | PQ | 33.5 |
Panoptic Segmentation | ScanNet | PanopticFusion | https://arxiv.org/abs/1903.01177v2 | PQ_th | 30.8 |
Panoptic Segmentation | ScanNet | PanopticFusion | https://arxiv.org/abs/1903.01177v2 | PQ_st | 58.4 |
Panoptic Segmentation | ScanNet | SceneGraphFusion | https://arxiv.org/abs/2103.14898v3 | PQ | 31.5 |
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