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VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse Conditions


Nov 22, 2022
Mingjia Li, Binhui Xie, Shuang Li, Chi Harold Liu, Xinjing Cheng

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* Camera ready for AAAI 2023. Code is available at https://github.com/BIT-DA/VBLC 

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EVA: Exploring the Limits of Masked Visual Representation Learning at Scale


Nov 14, 2022
Yuxin Fang, Wen Wang, Binhui Xie, Quan Sun, Ledell Wu, Xinggang Wang, Tiejun Huang, Xinlong Wang, Yue Cao

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* EVA Unit-01 Launched! 

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Joint Semantic Transfer Network for IoT Intrusion Detection


Oct 28, 2022
Jiashu Wu, Yang Wang, Binhui Xie, Shuang Li, Hao Dai, Kejiang Ye, Chengzhong Xu

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* Accepted by IEEE Internet of Things Journal 

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SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation


Apr 19, 2022
Binhui Xie, Shuang Li, Mingjia Li, Chi Harold Liu, Gao Huang, Guoren Wang

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* 16 pages, code is available at https://github.com/BIT-DA/SePiCo 

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Active Learning for Domain Adaptation: An Energy-based Approach


Dec 08, 2021
Binhui Xie, Longhui Yuan, Shuang Li, Chi Harold Liu, Xinjing Cheng, Guoren Wang

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* Accepted by AAAI 2022. Code is available at https://github.com/BIT-DA/EADA 

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Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation


Nov 25, 2021
Binhui Xie, Longhui Yuan, Shuang Li, Chi Harold Liu, Xinjing Cheng

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* 18 pages 

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SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning


Nov 24, 2021
Binhui Xie, Kejia Yin, Shuang Li, Xinjing Chen

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* 15 pages; The code is publicly available at https://github.com/BinhuiXie/SPCL 

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Semantic Distribution-aware Contrastive Adaptation for Semantic Segmentation


May 11, 2021
Shuang Li, Binhui Xie, Bin Zang, Chi Harold Liu, Xinjing Cheng, Ruigang Yang, Guoren Wang

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* 15 pages 

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Generalized Domain Conditioned Adaptation Network


Mar 23, 2021
Shuang Li, Binhui Xie, Qiuxia Lin, Chi Harold Liu, Gao Huang, Guoren Wang

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* Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI). Journal version of arXiv:2005.06717 (AAAI 2020). Code is available at https://github.com/BIT-DA/GDCAN 

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