Instance Segmentation On Lvis V1 0 Val
평가 지표
mask AP
mask APr
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | mask AP | mask APr |
|---|---|---|
| exploring-plain-vision-transformer-backbones | 48.1 | 36.9 |
| equalization-loss-v2-a-new-gradient-balance | 27.5 | - |
| adaptive-parametric-activation | 29.1 | 21.6 |
| fractal-calibration-for-long-tailed-object | 33.6 | 27.8 |
| diffusioninst-diffusion-model-for-instance | 22.3 | - |
| adaptive-parametric-activation | 30.7 | 23.6 |
| diffusioninst-diffusion-model-for-instance | 36 | - |
| exploring-plain-vision-transformer-backbones | 46.0 | 34.3 |
| diffusioninst-diffusion-model-for-instance | 38.6 | - |
| general-object-foundation-model-for-images | 49.9 | - |
| long-tailed-instance-segmentation-using | 27.7 | - |
| exploring-classification-equilibrium-in-long | 28 | - |
| divergen-improving-instance-segmentation-by | 45.5 | 45.8 |
| equalization-loss-v2-a-new-gradient-balance | 23.7 | - |
| x-paste-revisit-copy-paste-at-scale-with-clip | 45.4 | 43.8 |
| simple-copy-paste-is-a-strong-data | 38.1 | - |
| detrs-with-collaborative-hybrid-assignments | 60.7 | - |
| exploring-classification-equilibrium-in-long | 26.6 | - |
| lvis-challenge-track-technical-report-1st | 50.4 | - |
| equalization-loss-v2-a-new-gradient-balance | 28.8 | - |
| long-tailed-instance-segmentation-using | 29.0 | - |
| fractal-calibration-for-long-tailed-object | 30.7 | 25.7 |
| eva-exploring-the-limits-of-masked-visual | 55.0 | - |
| diffusioninst-diffusion-model-for-instance | 27 | - |