7 citations · 12 across the 4 of their papers we have counts for
4 papers
SLAMs: Semantic Learning based Activation Map for Weakly Supervised Semantic Segmentation
Junliang Chen, Xiaodong Zhao, Minmin Liu +1
Recent mainstream weakly-supervised semantic segmentation (WSSS) approaches mainly relies on image-level classification learning, which has limited representation capacity. In this…
SemFormer: Semantic Guided Activation Transformer for Weakly Supervised Semantic Segmentation
Junliang Chen, Xiaodong Zhao, Cheng Luo +1
Recent mainstream weakly supervised semantic segmentation (WSSS) approaches are mainly based on Class Activation Map (CAM) generated by a CNN (Convolutional Neural Network) based i…
Delving into the Scale Variance Problem in Object Detection
Junliang Chen, Xiaodong Zhao, Linlin Shen
Object detection has made substantial progress in the last decade, due to the capability of convolution in extracting local context of objects. However, the scales of objects are d…
Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic Segmentation
Jinheng Xie, Jianfeng Xiang, Junliang Chen +3
While class activation map (CAM) generated by image classification network has been widely used for weakly supervised object localization (WSOL) and semantic segmentation (WSSS), s…