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 ⌀ |
|---|---|---|---|---|---|
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | Qwen-VL-Max | https://arxiv.org/abs/2308.12966v3 | CIDEr | 201.47 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | Qwen-VL-Max | https://arxiv.org/abs/2308.12966v3 | SPICE | 26.13 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | Qwen-VL-Max | https://arxiv.org/abs/2308.12966v3 | Detection | 1.05 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | Qwen-VL-Max | https://arxiv.org/abs/2308.12966v3 | ACC | 40.33 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | Qwen-VL-Max | https://arxiv.org/abs/2308.12966v3 | #Learning Samples (N) | 16 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | GLM-4V | https://arxiv.org/abs/2311.03079v2 | BLEU-4 | 14.45 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | GLM-4V | https://arxiv.org/abs/2311.03079v2 | METEOR | 17.53 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | GLM-4V | https://arxiv.org/abs/2311.03079v2 | ROUGE-L | 24.28 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | GLM-4V | https://arxiv.org/abs/2311.03079v2 | CIDEr | 127.37 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | GLM-4V | https://arxiv.org/abs/2311.03079v2 | SPICE | 17.70 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | GLM-4V | https://arxiv.org/abs/2311.03079v2 | Detection | 0.89 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | GLM-4V | https://arxiv.org/abs/2311.03079v2 | ACC | 34.23 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | GLM-4V | https://arxiv.org/abs/2311.03079v2 | #Learning Samples (N) | 16 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | VCIN | http://openaccess.thecvf.com//content/ICCV2023/html/Xue_Variational_Causal_Inference_Network_for_Explanatory_Visual_Question_Answering_ICCV_2023_paper.html | BLEU-4 | 9.17 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | VCIN | http://openaccess.thecvf.com//content/ICCV2023/html/Xue_Variational_Causal_Inference_Network_for_Explanatory_Visual_Question_Answering_ICCV_2023_paper.html | METEOR | 19.82 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | VCIN | http://openaccess.thecvf.com//content/ICCV2023/html/Xue_Variational_Causal_Inference_Network_for_Explanatory_Visual_Question_Answering_ICCV_2023_paper.html | ROUGE-L | 33.34 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | VCIN | http://openaccess.thecvf.com//content/ICCV2023/html/Xue_Variational_Causal_Inference_Network_for_Explanatory_Visual_Question_Answering_ICCV_2023_paper.html | CIDEr | 4.28 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | VCIN | http://openaccess.thecvf.com//content/ICCV2023/html/Xue_Variational_Causal_Inference_Network_for_Explanatory_Visual_Question_Answering_ICCV_2023_paper.html | SPICE | 13.39 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | VCIN | http://openaccess.thecvf.com//content/ICCV2023/html/Xue_Variational_Causal_Inference_Network_for_Explanatory_Visual_Question_Answering_ICCV_2023_paper.html | Detection | 0.28 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | VCIN | http://openaccess.thecvf.com//content/ICCV2023/html/Xue_Variational_Causal_Inference_Network_for_Explanatory_Visual_Question_Answering_ICCV_2023_paper.html | ACC | 17.77 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | VCIN | http://openaccess.thecvf.com//content/ICCV2023/html/Xue_Variational_Causal_Inference_Network_for_Explanatory_Visual_Question_Answering_ICCV_2023_paper.html | #Learning Samples (N) | 16 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | REX | https://arxiv.org/abs/2203.06107v1 | BLEU-4 | 0.00 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | REX | https://arxiv.org/abs/2203.06107v1 | METEOR | 4.37 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | REX | https://arxiv.org/abs/2203.06107v1 | ROUGE-L | 23.23 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | REX | https://arxiv.org/abs/2203.06107v1 | CIDEr | 0.89 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | REX | https://arxiv.org/abs/2203.06107v1 | SPICE | 0.00 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | REX | https://arxiv.org/abs/2203.06107v1 | Detection | 0.00 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | REX | https://arxiv.org/abs/2203.06107v1 | ACC | 17.77 |
Visual Question Answering > Explanatory Visual Question Answering > FS-MEVQA | SME | REX | https://arxiv.org/abs/2203.06107v1 | #Learning Samples (N) | 16 |
Event Segmentation | Kinetics-400 | CASTANET+ Ensemble | https://arxiv.org/abs/2107.00239v1 | F1 | 83.3 |
Event Segmentation > Generic Event Boundary Detection | Kinetics-GEBD | FlowGEBD | https://arxiv.org/abs/2404.18935v1 | F1 @ RelDis. 0.05 | 0.713 |
Event Segmentation > Generic Event Boundary Detection | TAPOS | FlowGEBD | https://arxiv.org/abs/2404.18935v1 | F1 @ RelDis. 0.05 | 0.375 |
Unsupervised Zero-Shot Panoptic Segmentation | COCO val2017 | U2Seg | https://arxiv.org/abs/2312.17243v1 | PQ | 11.1 |
Unsupervised Zero-Shot Panoptic Segmentation | COCO val2017 | U2Seg | https://arxiv.org/abs/2312.17243v1 | SQ | 60.1 |
Unsupervised Zero-Shot Panoptic Segmentation | COCO val2017 | U2Seg | https://arxiv.org/abs/2312.17243v1 | RQ | 13.7 |
Point Cloud Completion | Completion3D | TopNet | http://openaccess.thecvf.com/content_CVPR_2019/html/Tchapmi_TopNet_Structural_Point_Cloud_Decoder_CVPR_2019_paper.html | Chamfer Distance | 14.25(?) |
Point Cloud Completion | Completion3D | PCN | https://arxiv.org/abs/1808.00671v3 | Chamfer Distance | 18.22(?) |
Point Cloud Completion | Completion3D | GRNet | https://arxiv.org/abs/2006.03761v4 | Chamfer Distance | 10.64(CD-L2) |
Point Cloud Completion | Completion3D | AtlasNet | http://arxiv.org/abs/1802.05384v3 | Chamfer Distance | 17.77(?) |
Point Cloud Completion | Completion3D | VRCNet | https://arxiv.org/abs/2104.10154v1 | Chamfer Distance | 8.12(CD-L2) |
Point Cloud Completion | Completion3D | PMP-Net++ | https://arxiv.org/abs/2202.09507v3 | Chamfer Distance | 7.97(CD-L2) |
Point Cloud Completion | Completion3D | SeedFormer | https://arxiv.org/abs/2207.10315v1 | Chamfer Distance | 6.74(PCN dataset) |
Point Cloud Completion | ShapeNet | ODGNet | https://ojs.aaai.org/index.php/AAAI/article/view/27845 | Chamfer Distance | 6.50 |
Point Cloud Completion | ShapeNet | ODGNet | https://ojs.aaai.org/index.php/AAAI/article/view/27845 | F-Score@1% | 0.833 |
Point Cloud Completion | ShapeNet | AdaPoinTr | https://arxiv.org/abs/2301.04545v1 | Chamfer Distance | 6.53 |
Point Cloud Completion | ShapeNet | AdaPoinTr | https://arxiv.org/abs/2301.04545v1 | F-Score@1% | 0.845 |
Point Cloud Completion | ShapeNet | PSCU | https://arxiv.org/abs/2303.08240v3 | Chamfer Distance | 7.04 |
Point Cloud Completion | ShapeNet | GTNet | https://link.springer.com/article/10.1007/s11263-023-01820-y | Chamfer Distance | 7.15 |
Point Cloud Completion | ShapeNet | SnowFlakeNet | https://arxiv.org/abs/2202.09367v3 | Chamfer Distance | 7.21 |
Point Cloud Completion | ShapeNet | GRNet | https://arxiv.org/abs/2006.03761v4 | Chamfer Distance | 8.81 |
Point Cloud Completion | ShapeNet | GRNet | https://arxiv.org/abs/2006.03761v4 | F-Score@1% | 0.708 |
Point Cloud Completion | ShapeNet | GRNet | https://arxiv.org/abs/2006.03761v4 | Chamfer Distance L2 | 2.723 |
Point Cloud Completion | ShapeNet | PCN | https://arxiv.org/abs/1808.00671v3 | Chamfer Distance | 9.636 |
Point Cloud Completion | ShapeNet | PCN | https://arxiv.org/abs/1808.00671v3 | F-Score@1% | 0.695 |
Point Cloud Completion | ShapeNet | PCN | https://arxiv.org/abs/1808.00671v3 | Chamfer Distance L2 | 4.016 |
Point Cloud Completion | ShapeNet | MSN | https://arxiv.org/abs/1912.00280v1 | Chamfer Distance | 9.969 |
Point Cloud Completion | ShapeNet | MSN | https://arxiv.org/abs/1912.00280v1 | F-Score@1% | 0.705 |
Point Cloud Completion | ShapeNet | MSN | https://arxiv.org/abs/1912.00280v1 | Chamfer Distance L2 | 4.758 |
Point Cloud Completion | ShapeNet | TestNet | http://arxiv.org/abs/1506.03134v2 | Chamfer Distance | 100 |
Point Cloud Completion | ShapeNet | PoinTr | https://arxiv.org/abs/2108.08839v1 | F-Score@1% | 0.748 |
Point Cloud Completion | ShapeNet | PoinTr | https://arxiv.org/abs/2108.08839v1 | Chamfer Distance L2 | 8.38 |
Point Cloud Completion | ShapeNet | SpareNet | https://arxiv.org/abs/2103.02535v3 | Earth Mover's Distance | 1.862 |
Point Cloud Completion | ShapeNet | SpareNet | https://arxiv.org/abs/2103.02535v3 | Frechet Point cloud Distance | 0.645 |
Point Cloud Completion | ShapeNet-ViPC | XMFNet | https://arxiv.org/abs/2209.09552v1 | Chamfer Distance | 1.443 |
Point Cloud Completion | ShapeNet-ViPC | CSDN | https://arxiv.org/abs/2208.00751v2 | Chamfer Distance | 2.570 |
Point Cloud Completion | ShapeNet-ViPC | ViPC | https://arxiv.org/abs/2104.05666v2 | Chamfer Distance | 3.308 |
Image-to-Text Retrieval | AIC-ICC | ERNIE-ViL2.0 | https://arxiv.org/abs/2209.15270v1 | Recall@1 | 33.7 |
Image-to-Text Retrieval | AIC-ICC | ERNIE-ViL2.0 | https://arxiv.org/abs/2209.15270v1 | Recall@5 | 52.1 |
Image-to-Text Retrieval | AIC-ICC | ERNIE-ViL2.0 | https://arxiv.org/abs/2209.15270v1 | Recall@10 | 60.0 |
Image-to-Text Retrieval | AIC-ICC | CMCL | https://arxiv.org/abs/2103.06561v6 | Recall@1 | 20.3 |
Image-to-Text Retrieval | AIC-ICC | CMCL | https://arxiv.org/abs/2103.06561v6 | Recall@5 | 37 |
Image-to-Text Retrieval | AIC-ICC | CMCL | https://arxiv.org/abs/2103.06561v6 | Recall@10 | 45.6 |
Image-to-Text Retrieval | Flickr30k | InternVL-G-FT (finetuned, w/o ranking) | https://arxiv.org/abs/2312.14238v3 | Recall@1 | 97.9 |
Image-to-Text Retrieval | Flickr30k | InternVL-G-FT (finetuned, w/o ranking) | https://arxiv.org/abs/2312.14238v3 | Recall@5 | 100 |
Image-to-Text Retrieval | Flickr30k | InternVL-G-FT (finetuned, w/o ranking) | https://arxiv.org/abs/2312.14238v3 | Recall@10 | 100 |
Image-to-Text Retrieval | Flickr30k | BLIP-2 ViT-G (zero-shot, 1K test set) | https://arxiv.org/abs/2301.12597v3 | Recall@1 | 97.6 |
Image-to-Text Retrieval | Flickr30k | BLIP-2 ViT-G (zero-shot, 1K test set) | https://arxiv.org/abs/2301.12597v3 | Recall@5 | 100 |
Image-to-Text Retrieval | Flickr30k | BLIP-2 ViT-G (zero-shot, 1K test set) | https://arxiv.org/abs/2301.12597v3 | Recall@10 | 100 |
Image-to-Text Retrieval | Flickr30k | ONE-PEACE (finetuned, w/o ranking) | https://arxiv.org/abs/2305.11172v1 | Recall@1 | 97.6 |
Image-to-Text Retrieval | Flickr30k | ONE-PEACE (finetuned, w/o ranking) | https://arxiv.org/abs/2305.11172v1 | Recall@5 | 100 |
Image-to-Text Retrieval | Flickr30k | ONE-PEACE (finetuned, w/o ranking) | https://arxiv.org/abs/2305.11172v1 | Recall@10 | 100 |
Image-to-Text Retrieval | Flickr30k | InternVL-C-FT (finetuned, w/o ranking) | https://arxiv.org/abs/2312.14238v3 | Recall@1 | 97.2 |
Image-to-Text Retrieval | Flickr30k | InternVL-C-FT (finetuned, w/o ranking) | https://arxiv.org/abs/2312.14238v3 | Recall@5 | 100 |
Image-to-Text Retrieval | Flickr30k | InternVL-C-FT (finetuned, w/o ranking) | https://arxiv.org/abs/2312.14238v3 | Recall@10 | 100 |
Image-to-Text Retrieval | Flickr30k | BLIP-2 ViT-L (zero-shot, 1K test set) | https://arxiv.org/abs/2301.12597v3 | Recall@1 | 96.9 |
Image-to-Text Retrieval | Flickr30k | BLIP-2 ViT-L (zero-shot, 1K test set) | https://arxiv.org/abs/2301.12597v3 | Recall@5 | 100 |
Image-to-Text Retrieval | Flickr30k | BLIP-2 ViT-L (zero-shot, 1K test set) | https://arxiv.org/abs/2301.12597v3 | Recall@10 | 100 |
Image-to-Text Retrieval | Flickr30k | ERNIE-ViL 2.0 | https://arxiv.org/abs/2209.15270v1 | Recall@1 | 96.1 |
Image-to-Text Retrieval | Flickr30k | ERNIE-ViL 2.0 | https://arxiv.org/abs/2209.15270v1 | Recall@5 | 99.9 |
Image-to-Text Retrieval | Flickr30k | ERNIE-ViL 2.0 | https://arxiv.org/abs/2209.15270v1 | Recall@10 | 100.0 |
Image-to-Text Retrieval | Flickr30k | ALBEF | https://arxiv.org/abs/2107.07651v2 | Recall@1 | 95.9 |
Image-to-Text Retrieval | Flickr30k | ALBEF | https://arxiv.org/abs/2107.07651v2 | Recall@5 | 99.8 |
Image-to-Text Retrieval | Flickr30k | ALBEF | https://arxiv.org/abs/2107.07651v2 | Recall@10 | 100.0 |
Image-to-Text Retrieval | Flickr30k | ALBEF | https://arxiv.org/abs/2301.04742v1 | Recall@1 | 92.6 |
Image-to-Text Retrieval | Flickr30k | ALBEF | https://arxiv.org/abs/2301.04742v1 | Recall@5 | 99.3 |
Image-to-Text Retrieval | Flickr30k | ALBEF | https://arxiv.org/abs/2301.04742v1 | Recall@10 | 99.9 |
Image-to-Text Retrieval | Flickr30k | UNITER | https://arxiv.org/abs/2301.04742v1 | Recall@1 | 87.3 |
Image-to-Text Retrieval | Flickr30k | UNITER | https://arxiv.org/abs/2301.04742v1 | Recall@5 | 98 |
Image-to-Text Retrieval | Flickr30k | UNITER | https://arxiv.org/abs/2301.04742v1 | Recall@10 | 99.2 |
Image-to-Text Retrieval | Flickr30k | GSMN | https://arxiv.org/abs/2106.02400v1 | Recall@1 | 76.4 |
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