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Small Objects Matters in Weakly-supervised Semantic Segmentation
Weakly-supervised semantic segmentation (WSSS) performs pixel-wise classification given only image-level labels for training.
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
D-Net: Learning for Distinctive Point Clouds by Self-Attentive Point Searching and Learnable Feature Fusion
Most of early methods selected the important points on 3D shapes by analyzing the intrinsic geometric properties of every single shape, which fails to capture the importance of points that distinguishes a shape from objects of other classes, i. e., the distinction of points.
