We try different methods to complete face segmentation:
- A CNN Cascade for Landmark Guided Semantic Part Segmentation. Models and more details please refer to Aaron Jackson's website. We add CRF as postprocessing. CRF is implemented by pydensecrf.
- On Face Segmentation, Face Swapping, and Face Perception. Original codes and models.
- Generate convex hull according to landmarks.
Before using all three methods we detect landmarks and crop the image. Instead of using landmarks detection network in A CNN Cascade for Landmark Guided Semantic Part Segmentation we use 2D-FAN to detect landmarks which works very well on large pose images. We also try different methods to crop the image.
- face_segment_part.py: A CNN Cascade for Landmark Guided Semantic Part Segmentation.
- face_segment_yuval.py: On Face Segmentation, Face Swapping, and Face Perception.
- face_segment_contour.py: Detected landmarks and get convex hull.
Please download caffe(minimum version: 1.0) for face_segment_yuval.py, download caffe-future for face_segment_part.py
Then run the following command in a terminal:
pip install -r requirements.txt
- face_segment_part:
No crf:
Add crf:
No crf:
Add crf:
- face_segment_yuval:
Model face_seg_fcn8s(size:500x500):
Model face_seg_fcn8s_300_no_aug(size:300x300):
Add crf to second model:
- face_segment_contour:
- Modify probability computation in face_segment_yuval.py
- Add speed test
- Add landmark detection
- Add image cropping
- Contour -> segment
- Unify code style
- Improve CRF results
- Add example images to README
- Compare results of all methods