real-world datasets
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Node Classification | 9 real-world datasets (average) | Average Ranking1.56 | 43 | |
| Feature Importance Explanation | Real-world datasets | Best Score97.8 | 12 | |
| AI-generated image detection | Real-world Datasets Chameleon, SynthWildX, WildRF Aggregate | Accuracy95.8 | 11 | |
| Reflective surface reconstruction | Real-world datasets | Time (h)0.5 | 10 | |
| Video Motion Magnification | Real-world Datasets | MANIQA Score (Baby Scene)0.7475 | 10 | |
| Single Image Reflection Removal | Five Real-world Datasets (Real20, Objects, Postcard, Wild, Nature) Average (494) (test) | PSNR27.21 | 9 | |
| Low-light image enhancement | Real-world datasets (MEF, LIME, DICM, NPE) (test) | MEF Score4.14 | 6 |
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