Segment object with only image labels and paying attention to entire parts of objects with COMNet
Segment object with only image labels and paying attention to entire parts of objects with COMNet
COMNet: Co-Occurrent Matching for Weakly Supervised Semantic Segmentation
arXiv paper abstract https://arxiv.org/abs/2309.16959
arXiv PDF paper https://arxiv.org/pdf/2309.16959.pdf
Image-level weakly supervised semantic segmentation is a challenging task that has been deeply studied in recent years.
Most of the common solutions exploit class activation map (CAM) to locate object regions.
However, such response maps generated by the classification network usually focus on discriminative object parts.
... propose a novel Co-Occurrent Matching Network (COMNet), which can promote the quality of the CAMs and enforce the network to pay attention to the entire parts of objects.
... perform inter-matching on paired images that contain common classes to enhance the corresponded areas, and construct intra-matching on a single image to propagate the semantic features across the object regions.
... show that ... network can effectively boost the performance of the baseline model and achieve new state-of-the-art performance.
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