1 citations · 5 across the 28 of their papers we have counts for
31 papers · 1 filter
EgoOmniWorld: Unifying Egocentric Understanding via Ego-Action-World Interactions
Songruo Chen, Yuqian Fu, Yu Li +7
Egocentric video understanding spans diverse capabilities, modalities, and evaluation formats, yet these are often studied in isolation despite their tight coupling in real-world i…
EgoProbe: Benchmarking Long-Range and Exact Memory in Streaming Egocentric Videos
Haokai Pang, Yuqian Fu, Yifei Wang +4
Egocentric video provides a continuous first-person record of everyday activities, making it a natural foundation for wearable AI assistants. Unlike offline video understanding, st…
MEMO: Multi-Level Entity-Aware Memory for Streaming Video Understanding
Yinying Li, Yuqian Fu, Yulin Dai +3
Streaming video understanding requires models to process unbounded visual streams while preserving rich visual semantics across vast temporal horizons, posing a fundamental challen…
Gaussian-JEPA: Joint-Embedding Predictive Learning for 3D Gaussian Splats
Bin Ren, Qi Ma, Yue Li +7
3D Gaussian Splatting (3DGS) represents 3D content with anisotropic primitives that jointly encode geometry and appearance. Fixed-budget encoders consume sampled observations of Ga…
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…
ObjectStream: Latent Objects as Memory Anchors for Streaming Video Understanding
Mingkang Dong, Muxin Pu, Jie Li +8
Streaming video understanding requires models to continuously retain useful visual evidence before future questions are known. Existing approaches primarily manage the growing visu…
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving
Yung-Hsu Yang, Luigi Piccinelli, Siyuan Li +8
Safe autonomous navigation requires a holistic understanding of dynamic environments, necessitating the simultaneous estimation of metric depth, semantic segmentation, and instance…
InterEdit: Navigating Text-Guided 3D Dyadic Human Motion Editing
Yebin Yang, Di Wen, Lei Qi +10
Text-guided 3D motion editing has seen success in single-person scenarios, but its extension to multi-person settings is less explored due to limited paired data and the complexity…
EgoIntent: A Pre-Outcome Micro-Step Benchmark for Understanding What, Why, and Next
Ye Pan, Chi Kit Wong, Yuanhuiyi Lyu +8
Egocentric video provides a natural modality for studying human behavior, but conventional visual understanding captures mainly observable scenes, objects, and actions rather than…
EgoSound: Benchmarking Sound Understanding in Egocentric Videos
Bingwen Zhu, Yuqian Fu, Qiaole Dong +6
Multimodal Large Language Models (MLLMs) have recently achieved remarkable progress in vision-language understanding. Yet, human perception is inherently multisensory, integrating…
Exo2EgoSyn: Unlocking Foundation Video Generation Models for Exocentric-to-Egocentric Video Synthesis
Mohammad Mahdi, Yuqian Fu, Nedko Savov +3
Foundation video generation models such as WAN 2.2 exhibit strong text- and image-conditioned synthesis abilities but remain constrained to the same-view generation setting. In thi…
CompTrack: Information Bottleneck-Guided Low-Rank Dynamic Token Compression for Point Cloud Tracking
Sifan Zhou, Yichao Cao, Jiahao Nie +4
3D single object tracking (SOT) in LiDAR point clouds is a critical task in computer vision and autonomous driving. Despite great success having been achieved, the inherent sparsit…
Multimodal Spatial Reasoning in the Large Model Era: A Survey and Benchmarks
Xu Zheng, Zihao Dongfang, Lutao Jiang +17
Humans possess spatial reasoning abilities that enable them to understand spaces through multimodal observations, such as vision and sound. Large multimodal reasoning models extend…
V-SAM: Marrying SAM2 with Multi-Prompt Experts for Cross-View Object Correspondence
Jiancheng Pan, Runze Wang, Tianwen Qian +7
Cross-view object correspondence, exemplified by the representative task of ego-exo object correspondence, aims to establish consistent associations of the same object across diffe…
RefAtomNet++: Advancing Referring Atomic Video Action Recognition using Multi-Trajectory Semantic Retrieval
Kunyu Peng, Di Wen, Jia Fu +9
Who is being described, where are they, and what are they doing? Referring Atomic Video Action Recognition (RAVAR) answers these questions jointly by grounding a natural-language r…
Are We Using the Right Benchmark: An Evaluation Framework for Visual Token Compression Methods
Chenfei Liao, Wensong Wang, Zichen Wen +10
Recent efforts to accelerate inference in Multimodal Large Language Models (MLLMs) have largely focused on visual token compression. The effectiveness of these methods is commonly…
EgoNight: Towards Egocentric Vision Understanding at Night with a Challenging Benchmark
Deheng Zhang, Yuqian Fu, Runyi Yang +9
Most existing benchmarks for understanding egocentric vision focus primarily on daytime scenarios, overlooking the low-light conditions that are inevitable in real-world applicatio…
Vision encoders should be image size agnostic and task driven
Nedyalko Prisadnikov, Danda Pani Paudel, Yuqian Fu +1
This position paper argues that the next generation of vision encoders should be image size agnostic and task driven. The source of our inspiration is biological. Not a structural…
EgoCross: Benchmarking Multimodal Large Language Models for Cross-Domain Egocentric Video Question Answering
Yanjun Li, Yuqian Fu, Tianwen Qian +5
Recent advances in Multimodal Large Language Models (MLLMs) have significantly pushed the frontier of egocentric video question answering (EgocentricQA). However, existing benchmar…
3D-MOOD: Lifting 2D to 3D for Monocular Open-Set Object Detection
Yung-Hsu Yang, Luigi Piccinelli, Mattia Segu +6
Monocular 3D object detection is valuable for various applications such as robotics and AR/VR. Existing methods are confined to closed-set settings, where the training and testing…
RAG-6DPose: Retrieval-Augmented 6D Pose Estimation via Leveraging CAD as Knowledge Base
Kuanning Wang, Yuqian Fu, Tianyu Wang +4
Accurate 6D pose estimation is key for robotic manipulation, enabling precise object localization for tasks like grasping. We present RAG-6DPose, a retrieval-augmented approach tha…
Cross-View Multi-Modal Segmentation @ Ego-Exo4D Challenges 2025
Yuqian Fu, Runze Wang, Yanwei Fu +2
In this report, we present a cross-view multi-modal object segmentation approach for the object correspondence task in the Ego-Exo4D Correspondence Challenges 2025. Given object qu…
CLiViS: Unleashing Cognitive Map through Linguistic-Visual Synergy for Embodied Visual Reasoning
Kailing Li, Qi'ao Xu, Tianwen Qian +3
Embodied Visual Reasoning (EVR) seeks to follow complex, free-form instructions based on egocentric video, enabling semantic understanding and spatiotemporal reasoning in dynamic e…
Domain-RAG: Retrieval-Guided Compositional Image Generation for Cross-Domain Few-Shot Object Detection
Yu Li, Xingyu Qiu, Yuqian Fu +8
Cross-Domain Few-Shot Object Detection (CD-FSOD) aims to detect novel objects with only a handful of labeled samples from previously unseen domains. While data augmentation and gen…