3 citations · 4 across the 11 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.CV2026
Reward-Guided Semantic Evolution for Test-time Adaptive Object Detection
Lihua Zhou, Mao Ye, Xiatian Zhu +7
Open-vocabulary object detection with vision-language models (VLMs) such as Grounding DINO suffers from performance degradation under test-time distribution shifts, primarily due t…
cs.CV2026
FACTOR: Counterfactual Training-Free Test-Time Adaptation for Open-Vocabulary Object Detection
Kaixiang Zhao, Mao Ye, Lihua Zhou +4
Open-vocabulary object detection often fails under distribution shifts, as it can be misled by spurious correlations between non-causal visual attributes (e.g., brightness, texture…
cs.CV2026
Source-Free Domain Adaptation with Vision-Language Prior
Song Tang, Yunxiang Bai, Wenxin Su +3
Source-Free Domain Adaptation (SFDA) seeks to adapt a source model, which is pre-trained on a supervised source domain, for a target domain, with only access to unlabeled target tr…