Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers
BCNet
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [BCNet, CVPR 2021]
This is the official pytorch implementation of BCNet built on the open-source detectron2.
Lei Ke, Yu-Wing Tai, Chi-Keung Tang
CVPR 2021
- Two-stage instance segmentation with state-of-the-art performance.
- Image formation as composition of two overlapping layers.
- Bilayer decoupling for the occluder and occludee.
- Efficacy on both the FCOS and Faster R-CNN detectors.
Under construction. Our code and pretrained model will be fully released in two months.
Visualization of Occluded Objects
Qualitative instance segmentation results of our BCNet, using ResNet-101-FPN and Faster R-CNN detector. The bottom row visualizes squared heatmap of contour and mask predictions by the two GCN layers for the occluder and occludee in the same ROI region specified by the red bounding box, which