Improve training of object segmentation with only boxes by using mask quality with BoxTeacher
Improve training of object segmentation with only boxes by using mask quality with BoxTeacher
BoxTeacher: Exploring High-Quality Pseudo Labels for Weakly Supervised Instance Segmentation
arXiv paper abstract https://arxiv.org/abs/2210.05174v1
arXiv PDF paper https://arxiv.org/pdf/2210.05174v1.pdf
Labeling objects with pixel-wise segmentation requires a huge amount of human labor compared to bounding boxes.
Most existing methods for weakly supervised instance segmentation focus on designing heuristic losses with priors from bounding boxes.
While ... find that box-supervised methods can produce some fine segmentation masks and ... wonder whether the detectors could learn from these fine masks while ignoring low-quality masks.
... present BoxTeacher, an efficient and end-to-end training framework ... which leverages a sophisticated teacher to generate high-quality masks as pseudo labels.
... estimate the quality of pseudo masks, and propose the noise-aware pixel loss and noise-reduced affinity loss to adaptively optimize the student with pseudo masks.
... achieves 34.4 mask AP and 35.4 mask AP with ResNet-50 and ResNet-101 ... which outperforms the previous state-of-the-art methods by a significant margin ...
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