Image
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Partial Multi-Label Learning | image | Average Precision82 | 48 | |
| Partial Multi-Label Learning | image | One-Error27.5 | 27 | |
| Partial Multi-Label Learning | image | Hamming Loss0.168 | 27 | |
| Partial Multi-Label Learning | image | Ranking Loss0.148 | 24 | |
| Machine Translation (English to Hindi) | Image (test) | BLEU0.0195 | 14 | |
| Machine Translation (Hindi to English) | Image (test) | BLEU Score12.14 | 14 | |
| Multi-label classification | Image | Subset Accuracy47.96 | 13 | |
| Multi-label Feature Selection | image | Macro-F187.93 | 11 | |
| Multi-label Feature Selection | image | CV Score3.5696 | 11 | |
| Multi-label Feature Selection | image (test) | HL21.48 | 11 | |
| Multi-label feature selection | image | OE16.98 | 11 | |
| Multi-label Feature Selection | image | AP81.11 | 11 | |
| Partial Multi-Label Learning | image avg.#CLs (4) | Coverage36.6 | 9 | |
| Partial Multi-Label Learning | image avg.#CLs 3 | Coverage26.7 | 9 | |
| Partial Multi-Label Learning | image avg.#CLs (2) | Coverage28.3 | 9 | |
| Tomographic Reconstruction | Image Ribosome 1 (test) | RRMSE0.12 | 9 | |
| Visual Search | 1k image (test) | Rel P@k94.4 | 9 | |
| Multi-label Feature Selection | IMAGE | Hamming Loss17.4 | 8 | |
| Multi-label Classification | Image | Execution Time (s)0.06 | 8 | |
| Multi-label classification | IMAGE | AP80.19 | 8 | |
| Multi-label classification | IMAGE | Ranking Loss0.17 | 8 | |
| Multi-label Feature Selection | IMAGE | Coverage40.13 | 8 | |
| Multi-label classification | IMAGE | Micro-F160.63 | 8 | |
| Clustering | image | AMI0.9311 | 6 | |
| Controllable Image Generation | 5,000-image Reconstruction (evaluation) | FID15.52 | 6 |
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