collaborators

5 papers

cs.CV2026

RankVR: Low-Rank Structure Perception and Value Recalibration for Robust Composed Image Retrieval

Jiale Huang, Zixu Li, Zhiheng Fu +3

Composed Image Retrieval (CIR) constitutes a pivotal paradigm requiring models to perform joint reasoning on reference images and modification texts. However, the prevalence of Noi…

cs.CV2026

INTENT: Invariance and Discrimination-aware Noise Mitigation for Robust Composed Image Retrieval

Zhiwei Chen, Yupeng Hu, Zhiheng Fu +4

Composed Image Retrieval (CIR) is a challenging image retrieval paradigm that enables to retrieve target images based on multimodal queries consisting of reference images and modif…

cs.CV2026

HABIT: Chrono-Synergia Robust Progressive Learning Framework for Composed Image Retrieval

Zixu Li, Yupeng Hu, Zhiwei Chen +4

Composed Image Retrieval (CIR) is a flexible image retrieval paradigm that enables users to accurately locate the target image through a multimodal query composed of a reference im…

cs.CV2026

ReTrack: Evidence-Driven Dual-Stream Directional Anchor Calibration Network for Composed Video Retrieval

Zixu Li, Yupeng Hu, Zhiwei Chen +4

With the rapid growth of video data, Composed Video Retrieval (CVR) has emerged as a novel paradigm in video retrieval and is receiving increasing attention from researchers. Unlik…

cs.CV2026

MELT: Improve Composed Image Retrieval via the Modification Frequentation-Rarity Balance Network

Guozhi Qiu, Zhiwei Chen, Zixu Li +4

Composed Image Retrieval (CIR) uses a reference image and a modification text as a query to retrieve a target image satisfying the requirement of ``modifying the reference image ac…