Ming Qi

The Active Cross-View Object Geo-Localization (ActiveGeo), where an agent sequentially selects new viewpoints and determines when to stop, aiming to improve localization with minimal observations is introduced, and an ActiveGeo framework with three-stage training is proposed.

CamoShift is the first to target both visual stealthiness and attack success in visible-infrared object detection, and is the first to target both visual stealthiness and attack success in visible-infrared object detection.

ACT is the first framework to study semi-supervised VIOD under this image-pair-level setting and forms consensus pseudo labels under pair-preserving views to recover branch-wise misses and supervise unlabeled pairs.

MVLGeo, an efficient framework designed to unify multiple viewpoints and reduce model redundancy, achieves state-of-the-art performance, demonstrating robustness to input degradation and generalization across viewpoints.