CenterFace: Joint Face Detection and Alignment Using Face as Point
Yuanyuan Xu, Wan Yan, Haixin Sun, Genke Yang, Jiliang Luo
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/Star-Clouds/CenterFaceOfficialIn papernone★ 0
- github.com/2023-MindSpore-4/Code8/tree/main/centerfacemindspore★ 0
- github.com/2023-MindSpore-1/ms-code-6/tree/main/centerfacemindspore★ 0
- github.com/mindspore-ai/models/tree/master/official/cv/centerfacemindspore★ 0
- github.com/2024-MindSpore-1/Code7/tree/main/centerfacemindspore★ 0
- github.com/ORB-HD/defacenone★ 0
- github.com/Mind23-2/MindCode-14mindspore★ 0
- github.com/MindSpore-paper-code-3/code6/tree/main/centerfacemindspore★ 0
- github.com/yangyucheng000/papermindspore★ 0
Abstract
Face detection and alignment in unconstrained environment is always deployed on edge devices which have limited memory storage and low computing power. This paper proposes a one-stage method named CenterFace to simultaneously predict facial box and landmark location with real-time speed and high accuracy. The proposed method also belongs to the anchor free category. This is achieved by: (a) learning face existing possibility by the semantic maps, (b) learning bounding box, offsets and five landmarks for each position that potentially contains a face. Specifically, the method can run in real-time on a single CPU core and 200 FPS using NVIDIA 2080TI for VGA-resolution images, and can simultaneously achieve superior accuracy (WIDER FACE Val/Test-Easy: 0.935/0.932, Medium: 0.924/0.921, Hard: 0.875/0.873 and FDDB discontinuous: 0.980, continuous: 0.732). A demo of CenterFace can be available at https://github.com/Star-Clouds/CenterFace.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| WIDER Face (Easy) | CenterFace | AP | 0.93 | — | Unverified |
| WIDER Face (Hard) | CenterFace | AP | 0.87 | — | Unverified |
| WIDER Face (Medium) | CenterFace | AP | 0.92 | — | Unverified |