78 citations · 79 across the 5 of their papers we have counts for
5 papers
Background Activation Suppression for Weakly Supervised Object Localization and Semantic Segmentation
Wei Zhai, Pingyu Wu, Kai Zhu +3
Weakly supervised object localization and semantic segmentation aim to localize objects using only image-level labels. Recently, a new paradigm has emerged by generating a foregrou…
Traffic Scene Parsing through the TSP6K Dataset
Peng-Tao Jiang, Yuqi Yang, Yang Cao +3
Traffic scene perception in computer vision is a critically important task to achieve intelligent cities. To date, most existing datasets focus on autonomous driving scenes. We obs…
Background Activation Suppression for Weakly Supervised Object Localization
Pingyu Wu, Wei Zhai, Yang Cao
Weakly supervised object localization (WSOL) aims to localize objects using only image-level labels. Recently a new paradigm has emerged by generating a foreground prediction map (…
Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning
Kai Zhu, Yang Cao, Wei Zhai +2
Few-shot class-incremental learning is to recognize the new classes given few samples and not forget the old classes. It is a challenging task since representation optimization and…
EGNet:Edge Guidance Network for Salient Object Detection
Jia-Xing Zhao, Jiangjiang Liu, Den-Ping Fan +3
Fully convolutional neural networks (FCNs) have shown their advantages in the salient object detection task. However, most existing FCNs-based methods still suffer from coarse obje…