3 papers
cs.CV2024
Domain-Conditioned Transformer for Fully Test-time Adaptation
Yushun Tang, Shuoshuo Chen, Jiyuan Jia +2
Fully test-time adaptation aims to adapt a network model online based on sequential analysis of input samples during the inference stage. We observe that, when applying a transform…
cs.CV2024
Dual-Path Adversarial Lifting for Domain Shift Correction in Online Test-time Adaptation
Yushun Tang, Shuoshuo Chen, Zhihe Lu +2
Transformer-based methods have achieved remarkable success in various machine learning tasks. How to design efficient test-time adaptation methods for transformer models becomes an…
cs.CV2024
Learning Visual Conditioning Tokens to Correct Domain Shift for Fully Test-time Adaptation
Yushun Tang, Shuoshuo Chen, Zhehan Kan +3
Fully test-time adaptation aims to adapt the network model based on sequential analysis of input samples during the inference stage to address the cross-domain performance degradat…