activity
20202026
most citedDeep Residual Correction Network for Partial Domain Adaptation

164 citations · 236 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Dynamic Resolution Routing for Efficient Egocentric Grounding

Huixin Sun, Wangbo Zhao, Fanyue Wei +3

Egocentric visual grounding requires high-resolution inputs to localize small objects. However, scaling Multimodal Large Language Models to this domain is constrained by the excess…

cs.CV2025

Online Test-time Adaptation for 3D Human Pose Estimation: A Practical Perspective with Estimated 2D Poses

Qiuxia Lin, Kerui Gu, Linlin Yang +1

Online test-time adaptation for 3D human pose estimation is used for video streams that differ from training data. Ground truth 2D poses are used for adaptation, but only estimated…

cs.CV2025

Semantics-aware Test-time Adaptation for 3D Human Pose Estimation

Qiuxia Lin, Rongyu Chen, Kerui Gu +1

This work highlights a semantics misalignment in 3D human pose estimation. For the task of test-time adaptation, the misalignment manifests as overly smoothed and unguided predicti…

cs.CV2021★ 69 cited

Generalized Domain Conditioned Adaptation Network

Shuang Li, Binhui Xie, Qiuxia Lin +3

Domain Adaptation (DA) attempts to transfer knowledge learned in the labeled source domain to the unlabeled but related target domain without requiring large amounts of target supe…

cs.CV2020★ 3 cited

Domain Conditioned Adaptation Network

Shuang Li, Chi Harold Liu, Qiuxia Lin +4

Tremendous research efforts have been made to thrive deep domain adaptation (DA) by seeking domain-invariant features. Most existing deep DA models only focus on aligning feature r…

cs.CV2020★ 164 cited

Deep Residual Correction Network for Partial Domain Adaptation

Shuang Li, Chi Harold Liu, Qiuxia Lin +4

Deep domain adaptation methods have achieved appealing performance by learning transferable representations from a well-labeled source domain to a different but related unlabeled t…