Improve the accuracy of Detection & Segmentation models by using SOTA recipes and primitives · Issue #5307 · pytorch/vision (original) (raw)

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Description

🚀 The feature

Similar to #3995 but focus on Object Detection and Segmentation.

Kick-off a Batteries Included phase 2 project that will focus on improving object detection and segmentation. After adding the necessary primitives, create a new recipe that improves the accuracy of existing models and retrain them to offer better weights to the community.

Results

Best currently available models achieved:

• RetinaNet ResNet50 FPN: Add RetinaNet improved weights #5756
  • Old retinanet_resnet50_fpn: 36.4 mAP
  • New retinanet_resnet50_fpn_v2: 41.5 mAP (+5.1)
• MaskRCNN ResNet50 FPN: Add MaskRCNN improved weights #5773
  • Old maskrcnn_resnet50_fpn: 37.9 box mAP / 34.6 mask mAP
  • New maskrcnn_resnet50_fpn_v2: 47.4 box mAP / 41.8 mask mAP (+9.5/+7.2)
• FasterRCNN ResNet50 FPN: Add FasterRCNN improved weights #5763
  • Old fasterrcnn_resnet50_fpn: 37.0 mAP
  • New fasterrcnn_resnet50_fpn_v2: 46.7 mAP (+9.7)

The above results were achieved by building on top of work done by @rbgirshick, @pdollar, @vaibhava0, @fmassa and @xiaohu2015.