1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
Frozen CLIP: A Strong Backbone for Weakly Supervised Semantic Segmentation
Bingfeng Zhang, Siyue Yu, Yunchao Wei +2
Weakly supervised semantic segmentation has witnessed great achievements with image-level labels. Several recent approaches use the CLIP model to generate pseudo labels for trainin…
eess.IV2024★ 1 cited
Modeling the Label Distributions for Weakly-Supervised Semantic Segmentation
Linshan Wu, Zhun Zhong, Jiayi Ma +4
Weakly-Supervised Semantic Segmentation (WSSS) aims to train segmentation models by weak labels, which is receiving significant attention due to its low annotation cost. Existing a…
cs.CV2023
CoinSeg: Contrast Inter- and Intra- Class Representations for Incremental Segmentation
Zekang Zhang, Guangyu Gao, Jianbo Jiao +2
Class incremental semantic segmentation aims to strike a balance between the model's stability and plasticity by maintaining old knowledge while adapting to new concepts. However,…