130 citations · 316 across the 18 of their papers we have counts for
4 papers · 1 filter
Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation
Yazhou Yao, Tao Chen, Guosen Xie +5
Semantic segmentation aims to classify every pixel of an input image. Considering the difficulty of acquiring dense labels, researchers have recently been resorting to weak labels…
Jo-SRC: A Contrastive Approach for Combating Noisy Labels
Yazhou Yao, Zeren Sun, Chuanyi Zhang +4
Due to the memorization effect in Deep Neural Networks (DNNs), training with noisy labels usually results in inferior model performance. Existing state-of-the-art methods primarily…
Semantically Meaningful Class Prototype Learning for One-Shot Image Semantic Segmentation
Tao Chen, Guosen Xie, Yazhou Yao +4
One-shot semantic image segmentation aims to segment the object regions for the novel class with only one annotated image. Recent works adopt the episodic training strategy to mimi…
Exploiting Web Images for Fine-Grained Visual Recognition by Eliminating Noisy Samples and Utilizing Hard Ones
Huafeng Liu, Chuanyi Zhang, Yazhou Yao +4
Labeling objects at a subordinate level typically requires expert knowledge, which is not always available when using random annotators. As such, learning directly from web images…