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 Object Super-Resolution > Super-Resolution > Image Rescaling | Set14-4x | IRN | https://arxiv.org/abs/2005.05650v1 | PSNR | 32.67 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | Set14-4x | IRN | https://arxiv.org/abs/2005.05650v1 | SSIM | 0.9015 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q90-4x | T-SAIN | https://arxiv.org/abs/2412.13508v1 | PSNR | 30.92 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q90-4x | T-SAIN | https://arxiv.org/abs/2412.13508v1 | SSIM | 0.8517 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q90-4x | SAIN | https://arxiv.org/abs/2303.02353v2 | PSNR | 30.31 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q90-4x | SAIN | https://arxiv.org/abs/2303.02353v2 | SSIM | 0.8367 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q90-4x | IRN | https://arxiv.org/abs/2005.05650v1 | PSNR | 28.42 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q90-4x | IRN | https://arxiv.org/abs/2005.05650v1 | SSIM | 0.7777 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q90-4x | HCFlow | https://arxiv.org/abs/2108.05301v1 | PSNR | 27.41 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q90-4x | HCFlow | https://arxiv.org/abs/2108.05301v1 | SSIM | 0.7485 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | Urban100-4x | IRN | https://arxiv.org/abs/2005.05650v1 | PSNR | 31.41 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | Urban100-4x | IRN | https://arxiv.org/abs/2005.05650v1 | SSIM | 0.9157 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | Urban100-4x | T-IRN | https://arxiv.org/abs/2412.13508v1 | PSNR | 31.19 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | Urban100-4x | T-IRN | https://arxiv.org/abs/2412.13508v1 | SSIM | 0.9132 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | Set14-2x | T-IRN | https://arxiv.org/abs/2412.13508v1 | PSNR | 41.70 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | Set14-2x | T-IRN | https://arxiv.org/abs/2412.13508v1 | SSIM | 0.9809 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | Set14-2x | IRN | https://arxiv.org/abs/2005.05650v1 | PSNR | 40.79 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | Set14-2x | IRN | https://arxiv.org/abs/2005.05650v1 | SSIM | 0.9778 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-2x | T-SAIN | https://arxiv.org/abs/2412.13508v1 | PSNR | 33.71 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-2x | T-SAIN | https://arxiv.org/abs/2412.13508v1 | SSIM | 0.9210 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-2x | SAIN | https://arxiv.org/abs/2303.02353v2 | PSNR | 33.17 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-2x | SAIN | https://arxiv.org/abs/2303.02353v2 | SSIM | 0.9082 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-2x | IRN | https://arxiv.org/abs/2005.05650v1 | PSNR | 30.20 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-2x | IRN | https://arxiv.org/abs/2005.05650v1 | SSIM | 0.8342 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-4x | T-SAIN | https://arxiv.org/abs/2412.13508v1 | PSNR | 29.43 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-4x | T-SAIN | https://arxiv.org/abs/2412.13508v1 | SSIM | 0.8237 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-4x | SAIN | https://arxiv.org/abs/2303.02353v2 | PSNR | 29.05 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-4x | SAIN | https://arxiv.org/abs/2303.02353v2 | SSIM | 0.8088 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-4x | IRN | https://arxiv.org/abs/2005.05650v1 | PSNR | 26.62 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-4x | IRN | https://arxiv.org/abs/2005.05650v1 | SSIM | 0.7096 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-4x | HCFlow | https://arxiv.org/abs/2108.05301v1 | PSNR | 26.38 |
3D Object Super-Resolution > Super-Resolution > Image Rescaling | DIV2K val-q50-4x | HCFlow | https://arxiv.org/abs/2108.05301v1 | SSIM | 0.7029 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | RefVSR-IR-ℓ1 | https://arxiv.org/abs/2203.14537v1 | PSNR | 34.86 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | RefVSR-ℓ1 | https://arxiv.org/abs/2203.14537v1 | PSNR | 34.74 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | RefVSR-small-ℓ1 | https://arxiv.org/abs/2203.14537v1 | PSNR | 33.88 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | IconVSR-ℓch [chan2021basicvsr] | https://arxiv.org/abs/2203.14537v1 | PSNR | 33.80 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | BasicVSR-ℓch [chan2021basicvsr] | https://arxiv.org/abs/2203.14537v1 | PSNR | 33.66 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | EDVR-ℓch [wang2019edvr] | https://arxiv.org/abs/2203.14537v1 | PSNR | 33.47 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | EDVR-M-ℓch [wang2019edvr] | https://arxiv.org/abs/2203.14537v1 | PSNR | 33.26 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | DCSR-ℓ1 [wang2021DCSR] | https://arxiv.org/abs/2203.14537v1 | PSNR | 32.43 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | RCAN-ℓ1 [zhang2018rcan] | https://arxiv.org/abs/2203.14537v1 | PSNR | 31.07 |
3D Object Super-Resolution > Super-Resolution > Reference-based Video Super-Resolution | RealMCVSR | TTSR-ℓ1 [yang2020TTSR] | https://arxiv.org/abs/2203.14537v1 | PSNR | 30.83 |
Personality Trait Recognition by Face | First Impressions v2 | R3D50 + EmoFormer cross-hemiface attention | https://www.sciencedirect.com/science/article/pii/S0957417423029433 | mAcc | 0.916 |
Personality Trait Recognition by Face | First Impressions v2 | R3D50 + EmoFormer cross-hemiface attention | https://www.sciencedirect.com/science/article/pii/S0957417423029433 | CCC | 0.634 |
Personality Trait Recognition by Face | First Impressions v2 | R2D34 + CR-Net | https://dl.acm.org/doi/10.1007/s11263-020-01309-y | mAcc | 0.913 |
Personality Trait Recognition by Face | First Impressions v2 | R2D101 + LSTM | https://www.sciencedirect.com/science/article/pii/S0262885621000688?via%3Dihub | mAcc | 0.913 |
Personality Trait Recognition by Face | First Impressions v2 | PML + SVM | https://ieeexplore.ieee.org/document/8014945/authors#authors | mAcc | 0.912 |
Personality Trait Recognition by Face | First Impressions v2 | ResNext + CNN-GRU, OpenFace + LSTNet | https://link.springer.com/article/10.1007/s12193-020-00347-7 | mAcc | 0.912 |
Personality Trait Recognition by Face | First Impressions v2 | R2D101 | https://aclanthology.org/2020.icon-main.42 | mAcc | 0.909 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LVLM | ChartVE | https://arxiv.org/abs/2312.10160v2 | Kendall's Tau-c | 0.178 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LVLM | GPT-4V | null | Kendall's Tau-c | 0.157 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LVLM | DePlot + GPT-4 | https://arxiv.org/abs/2212.10505v2 | Kendall's Tau-c | 0.129 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LVLM | LLaVA-1.5-13B | https://arxiv.org/abs/2310.03744v2 | Kendall's Tau-c | 0.002 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LVLM | Bard (before Gemini) | null | Kendall's Tau-c | -0.014 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-FT | Bard (before Gemini) | null | Kendall's Tau-c | 0.291 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-FT | ChartVE | https://arxiv.org/abs/2312.10160v2 | Kendall's Tau-c | 0.215 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-FT | GPT-4V | null | Kendall's Tau-c | 0.215 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-FT | LLaVA-1.5-13B | https://arxiv.org/abs/2310.03744v2 | Kendall's Tau-c | 0.214 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-FT | DePlot + GPT-4 | https://arxiv.org/abs/2212.10505v2 | Kendall's Tau-c | 0.109 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE | ChartVE | https://arxiv.org/abs/2312.10160v2 | Kendall's Tau-c | 0.178 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LLM | GPT-4V | https://arxiv.org/abs/2303.08774v5 | Kendall's Tau-c | 0.205 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LLM | DePlot + GPT-4 | https://arxiv.org/abs/2212.10505v2 | Kendall's Tau-c | 0.117 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LLM | Bard | null | Kendall's Tau-c | 0.105 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LLM | ChartVE | https://arxiv.org/abs/2312.10160v2 | Kendall's Tau-c | 0.091 |
Factual Inconsistency Detection in Chart Captioning | CHOCOLATE-LLM | LLaVA-1.5-13B | https://arxiv.org/abs/2310.03744v2 | Kendall's Tau-c | 0.057 |
Ordinal Classification | OASIS+NACC+ICBM+ABIDE+IXI | ResNet-18 | https://arxiv.org/abs/2403.10522v2 | Mean absolute error | 2.56 |
Conversational Web Navigation | WebLINX | Llama-2-13B | https://arxiv.org/abs/2402.05930v2 | Overall score | 25.21 |
Conversational Web Navigation | WebLINX | Llama-2-13B | https://arxiv.org/abs/2402.05930v2 | Intent Match | 81.91 |
Conversational Web Navigation | WebLINX | Llama-2-13B | https://arxiv.org/abs/2402.05930v2 | Element (IoU) | 22.82 |
Conversational Web Navigation | WebLINX | Llama-2-13B | https://arxiv.org/abs/2402.05930v2 | Text (F1) | 26.60 |
Conversational Web Navigation | WebLINX | S-LLaMA-2.7B | https://arxiv.org/abs/2402.05930v2 | Overall score | 25.02 |
Conversational Web Navigation | WebLINX | S-LLaMA-2.7B | https://arxiv.org/abs/2402.05930v2 | Intent Match | 84.00 |
Conversational Web Navigation | WebLINX | S-LLaMA-2.7B | https://arxiv.org/abs/2402.05930v2 | Element (IoU) | 22.60 |
Conversational Web Navigation | WebLINX | S-LLaMA-2.7B | https://arxiv.org/abs/2402.05930v2 | Text (F1) | 27.17 |
Conversational Web Navigation | WebLINX | Llama-2-7B | https://arxiv.org/abs/2402.05930v2 | Overall score | 24.57 |
Conversational Web Navigation | WebLINX | Llama-2-7B | https://arxiv.org/abs/2402.05930v2 | Intent Match | 82.64 |
Conversational Web Navigation | WebLINX | Llama-2-7B | https://arxiv.org/abs/2402.05930v2 | Element (IoU) | 22.26 |
Conversational Web Navigation | WebLINX | Llama-2-7B | https://arxiv.org/abs/2402.05930v2 | Text (F1) | 26.50 |
Conversational Web Navigation | WebLINX | Flan-T5-3B | https://arxiv.org/abs/2402.05930v2 | Overall score | 23.77 |
Conversational Web Navigation | WebLINX | Flan-T5-3B | https://arxiv.org/abs/2402.05930v2 | Intent Match | 81.14 |
Conversational Web Navigation | WebLINX | Flan-T5-3B | https://arxiv.org/abs/2402.05930v2 | Element (IoU) | 20.31 |
Conversational Web Navigation | WebLINX | Flan-T5-3B | https://arxiv.org/abs/2402.05930v2 | Text (F1) | 25.75 |
Conversational Web Navigation | WebLINX | S-LLaMA-1.3B | https://arxiv.org/abs/2402.05930v2 | Overall score | 23.73 |
Conversational Web Navigation | WebLINX | S-LLaMA-1.3B | https://arxiv.org/abs/2402.05930v2 | Intent Match | 83.32 |
Conversational Web Navigation | WebLINX | S-LLaMA-1.3B | https://arxiv.org/abs/2402.05930v2 | Element (IoU) | 20.54 |
Conversational Web Navigation | WebLINX | S-LLaMA-1.3B | https://arxiv.org/abs/2402.05930v2 | Text (F1) | 25.85 |
Conversational Web Navigation | WebLINX | GPT-3.5F | https://arxiv.org/abs/2402.05930v2 | Overall score | 21.22 |
Conversational Web Navigation | WebLINX | GPT-3.5F | https://arxiv.org/abs/2402.05930v2 | Intent Match | 77.56 |
Conversational Web Navigation | WebLINX | GPT-3.5F | https://arxiv.org/abs/2402.05930v2 | Element (IoU) | 18.64 |
Conversational Web Navigation | WebLINX | GPT-3.5F | https://arxiv.org/abs/2402.05930v2 | Text (F1) | 22.39 |
Conversational Web Navigation | WebLINX | MindAct-3B | https://arxiv.org/abs/2402.05930v2 | Overall score | 20.94 |
Conversational Web Navigation | WebLINX | MindAct-3B | https://arxiv.org/abs/2402.05930v2 | Intent Match | 79.89 |
Conversational Web Navigation | WebLINX | MindAct-3B | https://arxiv.org/abs/2402.05930v2 | Element (IoU) | 16.50 |
Conversational Web Navigation | WebLINX | MindAct-3B | https://arxiv.org/abs/2402.05930v2 | Text (F1) | 23.16 |
Conversational Web Navigation | WebLINX | Fuyu-8B | https://arxiv.org/abs/2402.05930v2 | Overall score | 19.97 |
Conversational Web Navigation | WebLINX | Fuyu-8B | https://arxiv.org/abs/2402.05930v2 | Intent Match | 80.07 |
Conversational Web Navigation | WebLINX | Fuyu-8B | https://arxiv.org/abs/2402.05930v2 | Element (IoU) | 15.70 |
Conversational Web Navigation | WebLINX | Fuyu-8B | https://arxiv.org/abs/2402.05930v2 | Text (F1) | 22.30 |
Conversational Web Navigation | WebLINX | Flan-T5-780M | https://arxiv.org/abs/2402.05930v2 | Overall score | 17.27 |
Conversational Web Navigation | WebLINX | Flan-T5-780M | https://arxiv.org/abs/2402.05930v2 | Intent Match | 80.02 |
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