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LightAIR: Lightweight Action Inversion and Riemannian Rectification for Text-based Person Anomaly Search
Yulun Zhang, Zixu Li, Zhiwei Chen +6
Traditional Text-based Person Search (TPS) is typically limited to matching static appearance attributes, severely neglecting dynamic action information. The Text-based Person Anom…
The First EgoCross Challenge at EgoVis 2026: Cross-Domain Egocentric Video Question Answering
Yuqian Fu, Tianwen Qian, Yanjun Li +30
EgoCross is a cross-domain egocentric video question answering benchmark designed to evaluate whether multimodal large language models can generalize beyond common daily-life scena…
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…
IMAGINE: Adaptive Schema-Imagery Enhanced Composition for Composed Video Retrieval
Jiale Huang, Zixu Li, Zhiwei Chen +3
Composed Video Retrieval (CVR) is designed to retrieve a target video that matches a reference video modified by a modification text. While existing methods explore cross-modal cor…
R^3: Composed Video Retrieval via Reasoning-Guided Recalling and Re-ranking
Zixu Li, Yupeng Hu, Zhiheng Fu +3
The CoVR-R challenge evaluates composed video retrieval, where a system must retrieve a target video from a large gallery given a reference video and a textual edit instruction. Th…
EgoAdapt: A Multi-Scene Egocentric Adaptation Method for CVPR 2026 HD-EPIC VQA Challenge
Zhiwei Chen, Yupeng Hu, Zixu Li +4
This technical report presents our solution, EgoAdapt (Egocentric Adaptation via Category, Calibration, and Consistency), to the CVPR 2026 HD-EPIC VQA challenge. HD-EPIC evaluates…
EgoAction: Egocentric Action Composition with Reliability-Aware Temporal Fusion for the EPIC-KITCHENS Action Detection Challenge at CVPR 2026
Zhiheng Fu, Zixu Li, Zhiwei Chen +4
The EPIC-KITCHENS-100 Action Detection challenge evaluates whether a model can localize the start and end of each action in long untrimmed egocentric videos and assign the correspo…
OmniEgo-R: A Routed Reasoning Framework for the 1st Cross-Domain EgoCross Challenge at CVPR 2026
Zixu Li, Zhiwei Chen, Zhiheng Fu +4
The 1st Cross-Domain EgoCross Challenge at EgoVis, CVPR 2026 evaluates whether multimodal large language models can reason over egocentric videos across surgery, industry, extreme…
TempRet: Temporal Enhancement and Two-Stage Reranking for CVPR 2026 EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge
Zixu Li, Yupeng Hu, Zhiwei Chen +4
Video-text retrieval has witnessed remarkable progress driven by large-scale vision-language pretraining, yet most existing approaches inherit an implicit assumption from image-tex…
COMBINER: Composed Image Retrieval Guided by Attribute-based Neighbor Relations
Zixu Li, Yupeng Hu, Zhiwei Chen +3
Composed Image Retrieval (CIR) represents a challenging retrieval task that targets locating specific images through multimodal inputs. Despite recent progress in CIR techniques, p…
TEMA: Anchor the Image, Follow the Text for Multi-Modification Composed Image Retrieval
Zixu Li, Yupeng Hu, Zhiheng Fu +3
Composed Image Retrieval (CIR) is an important image retrieval paradigm that enables users to retrieve a target image using a multimodal query that consists of a reference image an…
ConeSep: Cone-based Robust Noise-Unlearning Compositional Network for Composed Image Retrieval
Zixu Li, Yupeng Hu, Zhiwei Chen +3
The Composed Image Retrieval (CIR) task provides a flexible retrieval paradigm via a reference image and modification text, but it heavily relies on expensive and error-prone tripl…
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…
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…
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…
HINT: Composed Image Retrieval with Dual-path Compositional Contextualized Network
Mingyu Zhang, Zixu Li, Zhiwei Chen +5
Composed Image Retrieval (CIR) is a challenging image retrieval paradigm. It aims to retrieve target images from large-scale image databases that are consistent with the modificati…
HUD: Hierarchical Uncertainty-Aware Disambiguation Network for Composed Video Retrieval
Zhiwei Chen, Yupeng Hu, Zixu Li +3
Composed Video Retrieval (CVR) is a challenging video retrieval task that utilizes multi-modal queries, consisting of a reference video and modification text, to retrieve the desir…
OFFSET: Segmentation-based Focus Shift Revision for Composed Image Retrieval
Zhiwei Chen, Yupeng Hu, Zixu Li +3
Composed Image Retrieval (CIR) represents a novel retrieval paradigm that is capable of expressing users' intricate retrieval requirements flexibly. It enables the user to give a m…
FineCIR: Explicit Parsing of Fine-Grained Modification Semantics for Composed Image Retrieval
Zixu Li, Zhiheng Fu, Yupeng Hu +3
Composed Image Retrieval (CIR) facilitates image retrieval through a multimodal query consisting of a reference image and modification text. The reference image defines the retriev…