| human-part-segmentation-on-cihp | UniHCP (finetune) | #3 | Mean IoU: 69.8 |
| human-part-segmentation-on-human3-6m | UniHCP (finetune) | #3 | mIoU: 65.95 |
| object-detection-on-crowdhuman-full-body | UniHCP (finetune) | #8 | AP: 92.5mMR: 41.6 |
| pedestrian-attribute-recognition-on-pa-100k | UniHCP (finetune) | #6 | Accuracy: 86.18 |
| pedestrian-attribute-recognition-on-peta | UniHCP (FT) | #1 | Accuracy: 88.78% |
| pedestrian-attribute-recognition-on-rapv2 | UniHCP (finetune) | #3 | Accuracy: 82.34 |
| pedestrian-detection-on-caltech | UniHCP (FT) | #18 | Heavy MR^-2: 27.2 |
| person-re-identification-on-cuhk03 | UniHCP (finetune) | #4 | MAP: 83.1 |
| person-re-identification-on-market-1501 | UniHCP (finetune) | #105 | mAP: 90.3 |
| person-re-identification-on-msmt17 | UniHCP (finetune) | #19 | mAP: 67.3 |
| pose-estimation-on-aic | UniHCP (finetune) | #4 | AP: 33.6 |
| pose-estimation-on-mpii-human-pose | UniHCP (FT) | #5 | PCKh-0.5: 93.2 |
| pose-estimation-on-ochuman | UniHCP (direct eval) | #2 | Test AP: 87.4 |
| semantic-segmentation-on-lip-val | UniHCP (finetune) | #3 | mIoU: 63.86% |