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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…
SpaceEra++: A Unified Framework Towards 3D Spatial Reasoning in Video
Weili Guan, Haoyu Zhang, Meng Liu +3
Visual-spatial understanding, defined as the ability to infer object relationships and scene layouts from visual inputs, is fundamental to downstream tasks such as robotic navigati…
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…
From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model
Bing Hu, Zaijing Li, Rui Shao +4
Vision-Language-Action (VLA) models often suffer from performance degradation under distribution shifts, as they struggle to learn generalized behavior representations across varyi…
JFAA: Technical Report for the EPIC-KITCHENS-100 Action Anticipation Challenge at EgoVis 2026
Qiaohui Chu, Haoyu Zhang, Yisen Feng +4
We propose JFAA, a JEPA-based Future Action Anticipation method for the EPIC-KITCHENS-100 (EK-100) Action Anticipation task. Inspired by the representation learning and future pred…
VISTA: Technical Report for the Ego4D Short-Term Object Interaction Anticipation at EgoVis 2026
Qiaohui Chu, Haoyu Zhang, Yisen Feng +4
We propose VISTA, a V-JEPA Integrated StillFast Temporal Anticipator for the Ego4D Short-Term Object Interaction Anticipation (STA) Challenge at EgoVis 2026. Given an egocentric vi…
OSGNet with MLLM Reranking @ Ego4D Episodic Memory Challenge 2026
Yisen Feng, Leigang Qu, Haoyu Zhang +5
In this report, we present our champion solutions for the Natural Language Queries and GoalStep tracks of the Ego4D Episodic Memory Challenge at CVPR 2026. Both tracks require accu…
Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation
Junjie Wang, Xinghua Lou, Jason Li +8
Text-to-Image (T2I) models and Unified Multimodal Models (UMMs) have achieved remarkable progress in visual generation. However, their reliance on a single-pass generation paradigm…
MARS: Technical Report for the CASTLE Challenge at EgoVis 2026
Haoyu Zhang, Qiaohui Chu, Yisen Feng +4
This report presents MARS, short for Multimodal Agentic Reasoning with Source selection, our system for the CASTLE Challenge at EgoVis 2026. Participants must answer 185 closed-for…
Detecting Deepfakes via Hamiltonian Dynamics
Harry Cheng, Ming-Hui Liu, Tianyi Wang +3
Driven by the rapid development of generative AI models, deepfake detectors are compelled to undergo periodic recalibration to capture newly developed synthetic artifacts. To break…
Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding
Chang Liu, Henghui Ding, Nikhila Ravi +40
This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, whi…
The 1st Winner for 5th PVUW MeViS-Text Challenge: Strong MLLMs Meet SAM3 for Referring Video Object Segmentation
Xusheng He, Canyang Wu, Jinrong Zhang +3
This report presents our winning solution to the 5th PVUW MeViS-Text Challenge. The track studies referring video object segmentation under motion-centric language expressions, whe…
Advancing Complex Video Object Segmentation via Tracking-Enhanced Prompt: The 1st Winner for 5th PVUW MOSE Challenge
Jinrong Zhang, Canyang Wu, Xusheng He +3
In the Complex Video Object Segmentation task, researchers are required to track and segment specific targets within cluttered environments, which rigorously tests a method's capab…
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…
Technical Report for Ego4D Long-Term Action Anticipation Challenge 2025
Qiaohui Chu, Haoyu Zhang, Yisen Feng +4
In this report, we present a novel three-stage framework developed for the Ego4D Long-Term Action Anticipation (LTA) task. Inspired by recent advances in foundation models, our met…
Spatial Understanding from Videos: Structured Prompts Meet Simulation Data
Haoyu Zhang, Meng Liu, Zaijing Li +4
Visual-spatial understanding, the ability to infer object relationships and layouts from visual input, is fundamental to downstream tasks such as robotic navigation and embodied in…
Object-Shot Enhanced Grounding Network for Egocentric Video
Yisen Feng, Haoyu Zhang, Meng Liu +2
Egocentric video grounding is a crucial task for embodied intelligence applications, distinct from exocentric video moment localization. Existing methods primarily focus on the dis…
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin
Yuchen Wang, Xuefeng Bai, Xiucheng Li +3
Adapting vision-language models (VLMs) to downstream tasks with pseudolabels has gained increasing attention. A major obstacle is that the pseudolabels generated by VLMs tend to be…
Embodied Crowd Counting
Runling Long, Yunlong Wang, Jia Wan +5
Occlusion is one of the fundamental challenges in crowd counting. In the community, various data-driven approaches have been developed to address this issue, yet their effectivenes…