Transcam: Transformer attention-based cam refinement for weakly supervised semantic segmentation
Weakly supervised semantic segmentation (WSSS) with only image-level supervision is a
challenging task. Most existing methods exploit Class Activation Maps (CAM) to generate
pixel-level pseudo labels for supervised training. However, due to the local receptive field of
Convolution Neural Networks (CNN), CAM applied to CNNs often suffers from partial
activation—highlighting the most discriminative part instead of the entire object area. In
order to capture both local features and global representations, the Conformer has been …
challenging task. Most existing methods exploit Class Activation Maps (CAM) to generate
pixel-level pseudo labels for supervised training. However, due to the local receptive field of
Convolution Neural Networks (CNN), CAM applied to CNNs often suffers from partial
activation—highlighting the most discriminative part instead of the entire object area. In
order to capture both local features and global representations, the Conformer has been …
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