29 citations · 33 across the 32 of their papers we have counts for
29 papers · 1 filter
VisualErase: Dual-Branch Visual Trajectory Redirection for Robust Concept Erasure in Text-to-Image Diffusion Models
Qianlong Xiang, Miao Zhang, Kun Wang +3
Concept erasure is essential for the safe deployment of text-to-image diffusion models, as they may reproduce harmful, copyrighted, or privacy-sensitive content learned from uncons…
MM-ContextFold: Context Folding for Multimodal Agentic Retrieval
Yang Tian, Fan Liu, Jingyuan Zhang +3
Multimodal Agentic Retrieval (MAR) requires agents to solve complex information-seeking tasks by iteratively invoking external tools. Typical frameworks such as ReAct maintain raw…
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…
FiRE: Enhancing MLLMs with Fine-Grained Context Learning for Complex Image Retrieval
Bohan Hou, Haoqiang Lin, Xuemeng Song +4
Due to their strong generalizable multimodal processing and reasoning capabilities, Multimodal Large Language Models (MLLMs) have demonstrated significant potential as universal im…
Diverse-Intent Multi-Turn Fashion Image Retrieval
Mingqiang Tang, Haokun Wen, Meng Liu +3
Real-world fashion search involves interactive retrieval across multiple turns. However, existing multi-turn retrieval methods are built on a restrictive assumption that every inte…
ParseFixer: An Agentic Framework for Document Parsing via Selective Multimodal Correction
LeKai Yu, Hao Liu, Kun Wang +4
In this report, we present our third-place solution for the DataMFM Challenge Track 1: Document Parsing. This track requires models to recover structured Markdown documents from do…
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…
ChartLens: A Dual-Branch Framework for Chart Data Correction and Factual Summary Refinement
Hao Liu, Ruping Cao, Kun Wang +4
In this report, we present our champion solution for the DataMFM Challenge Track 2: Chart Understanding. This track requires models to recover structured chart data and generate fa…
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…
Air-Know: Arbiter-Calibrated Knowledge-Internalizing Robust Network for Composed Image Retrieval
Zhiheng Fu, Yupeng Hu, Qianyun Yang +3
Composed Image Retrieval (CIR) has attracted significant attention due to its flexible multimodal query method, yet its development is severely constrained by the Noisy Triplet Cor…
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…
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…
NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results
Andrey Moskalenko, Alexey Bryncev, Ivan Kosmynin +40
This paper presents an overview of the NTIRE 2026 Challenge on Video Saliency Prediction. The goal of the challenge participants was to develop automatic saliency map prediction me…
ViSAGE @ NTIRE 2026 Challenge on Video Saliency Prediction
Kun Wang, Yupeng Hu, Zhiran Li +3
In this report, we present our champion solution for the NTIRE 2026 Challenge on Video Saliency Prediction held in conjunction with CVPR 2026. To exploit complementary inductive bi…
StructAlign: Structured Cross-Modal Alignment for Continual Text-to-Video Retrieval
Shaokun Wang, Weili Guan, Jizhou Han +3
Continual Text-to-Video Retrieval (CTVR) is a challenging multimodal continual learning setting, where models must incrementally learn new semantic categories while maintaining acc…
Open Multimodal Retrieval-Augmented Factual Image Generation
Yang Tian, Fan Liu, Jingyuan Zhang +3
Large Multimodal Models (LMMs) have achieved remarkable progress in generating photorealistic and prompt-aligned images, but they often produce outputs that contradict verifiable k…