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Models/Parsing R-CNN + ResNext101

Parsing R-CNN + ResNext101

Reported on 7 benchmarks across 5 tasks · 1 paper · 7 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision3 results

Pose EstimationonDensePose-COCO
AP· 2018-11-30
61.6
best: 68 (DP-RCNN-DeepLab (ResNet-101))
SOTA
Parsing R-CNN for Instance-Level Human Analysis arXiv:1811.12596
Human Part SegmentationonMHP v2.0
Mean IoU· 2018-11-30
41.8
SOTA
Parsing R-CNN for Instance-Level Human Analysis arXiv:1811.12596
Human Part SegmentationonCIHP
Mean IoU· 2018-11-30
61.1
best: 72.68 (Hulk(Finetune, ViT-L))
SOTA
Parsing R-CNN for Instance-Level Human Analysis arXiv:1811.12596

Audio3 results

2D Semantic SegmentationonMHP v2.0
Mean IoU· 2018-11-30
41.8
SOTA
Parsing R-CNN for Instance-Level Human Analysis arXiv:1811.12596
2D Semantic SegmentationonCIHP
Mean IoU· 2018-11-30
61.1
best: 72.68 (Hulk(Finetune, ViT-L))
SOTA
Parsing R-CNN for Instance-Level Human Analysis arXiv:1811.12596
1 Image, 2*2 StitchionDensePose-COCO
AP· 2018-11-30
61.6
best: 68 (DP-RCNN-DeepLab (ResNet-101))
SOTA
Parsing R-CNN for Instance-Level Human Analysis arXiv:1811.12596

Methodology1 result

3DonDensePose-COCO
AP· 2018-11-30
61.6
best: 68 (DP-RCNN-DeepLab (ResNet-101))
SOTA
Parsing R-CNN for Instance-Level Human Analysis arXiv:1811.12596