via “semantic face region segmentation with segformer architecture”
image-segmentation model by undefined. 2,32,614 downloads.
Unique: Uses SegFormer (NVIDIA/MIT-B5) transformer backbone with hierarchical feature fusion instead of traditional FCN/DeepLab CNN architectures, enabling better long-range facial structure understanding and achieving state-of-the-art accuracy on CelebAMask-HQ (56.8% mIoU). Provides both PyTorch and ONNX exports for flexible deployment across cloud, edge, and browser environments via transformers.js.
vs others: Outperforms BiSeNet and DeepLabV3+ on facial region accuracy while maintaining smaller model size (85MB) compared to ResNet-101 based alternatives, and offers native ONNX support for browser/mobile deployment that competing face-parsing models lack.