Undoing the Damage of Label Shift for Cross-domain Semantic Segmentation

12 April 2022

Papers citing "Undoing the Damage of Label Shift for Cross-domain Semantic Segmentation"

8 / 8 papers shown

Title
Federated Class-Incremental Learning: A Hybrid Approach Using Latent Exemplars and Data-Free Techniques to Address Local and Global Forgetting Milad Khademi Nori Il Kim Guanghui CLL 67 1 0 26 Jan 2025
Lift, Splat, Map: Lifting Foundation Masks for Label-Free Semantic Scene Completion Arthur Zhang Rainier Heijne Joydeep Biswas 31 1 0 03 Jul 2024
Federated Class-Incremental Learning Jiahua Dong Lixu Wang Zhen Fang Gan Sun Shichao Xu Tianlin Li Qi Zhu CLL FedML 24 168 0 22 Mar 2022
Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation Zhedong Zheng Yi Yang NoLa 191 497 0 08 Mar 2020
Unbiased Mean Teacher for Cross-domain Object Detection Jinhong Deng Wen Li Yuhua Chen Lixin Duan 79 286 0 02 Mar 2020
Confidence Regularized Self-Training Yang Zou Zhiding Yu Xiaofeng Liu B. Kumar Jinsong Wang 233 789 0 26 Aug 2019
Deep High-Resolution Representation Learning for Visual Recognition Jingdong Wang Ke Sun Tianheng Cheng Borui Jiang Chaorui Deng ... Yadong Mu Mingkui Tan Xinggang Wang Wenyu Liu Bin Xiao 195 3,531 0 20 Aug 2019
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 446 15,639 0 02 Nov 2015