26 citations · 94 across the 20 of their papers we have counts for
6 papers · 1 filter
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…
Weakly-Supervised Action Localization by Hierarchically-structured Latent Attention Modeling
Guiqin Wang, Peng Zhao, Cong Zhao +5
Weakly-supervised action localization aims to recognize and localize action instancese in untrimmed videos with only video-level labels. Most existing models rely on multiple insta…
Automotive Object Detection via Learning Sparse Events by Spiking Neurons
Hu Zhang, Yanchen Li, Luziwei Leng +5
Event-based sensors, distinguished by their high temporal resolution of 1 and a dynamic range of 120 , stand out as ideal tools for deployment in fast…
Cross-Inferential Networks for Source-free Unsupervised Domain Adaptation
Yushun Tang, Qinghai Guo, Zhihai He
One central challenge in source-free unsupervised domain adaptation (UDA) is the lack of an effective approach to evaluate the prediction results of the adapted network model in th…
Accurate and Efficient Event-based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network
Rui Zhang, Luziwei Leng, Kaiwei Che +5
Spiking neural networks (SNNs), known for their low-power, event-driven computation and intrinsic temporal dynamics, are emerging as promising solutions for processing dynamic, asy…
Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation
Yushun Tang, Ce Zhang, Heng Xu +5
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…