Papers › Face Detection Using Improved Faster RCNN
Face Detection Using Improved Faster RCNN
Changzheng Zhang, Xiang Xu, Dandan Tu
Faster RCNN has achieved great success for generic object detection including PASCAL object detection and MS COCO object detection. In this report, we propose a detailed designed Faster RCNN method named FDNet1.0 for face detection. Several techniques were employed including multi-scale training, multi-scale testing, light-designed RCNN, some tricks for inference and a vote-based ensemble method. Our method achieves two 1th places and one 2nd place in three tasks over WIDER FACE validation dataset (easy set, medium set, hard set).
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Face Detection | WIDER Face (Easy) | FDNet | AP | 0.950 | #16 of 27 | Archive leaderboard | report |
| Face Detection | WIDER Face (Hard) | FDNet | AP | 0.896 | #8 of 40 | Archive leaderboard | report |
| Face Detection | WIDER Face (Medium) | FDNet | AP | 0.939 | #15 of 37 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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