41 citations · 50 across the 21 of their papers we have counts for
24 papers
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…
WM-R1: Training GUI Agents to Reason and leverage World Models with Reinforcement Learning
Yu Han, Tianwen Qian
GUI agents trained with reinforcement learning (RL) have showcased strong environment learning capabilities on mobile platforms. However, RL typically demands extensive real-enviro…
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…
3SPO: State-Score-Supervised Policy Optimization for LLM Agents
Yu Han, Kailing Li, Yang Jiao +4
Training large language models (LLMs) as autonomous agents via reinforcement learning (RL) has enabled frontier models to achieve superhuman performance in long-horizon tasks. Howe…
Afford-VLA: Action-Aligned Visual Planning via Internalized Affordance
Runze Wang, Yuqian Fu, Yu Li +7
Vision-language-action (VLA) models have shown strong potential for generalist robot manipulation, yet they remain limited by insufficient spatial reasoning, particularly in determ…
SpatialImaginer: Towards Adaptive Visual Imagination for Spatial Reasoning
Yian Li, Yang Jiao, Bin Zhu +4
Spatial intelligence, which refers to the ability to reason about geometric and physical structure from visual observations, remains a core challenge for multimodal large language…
Think, Then Verify: A Hypothesis-Verification Multi-Agent Framework for Long Video Understanding
Zheng Wang, Haoran Chen, Haoxuan Qin +3
Long video understanding is challenging due to dense visual redundancy, long-range temporal dependencies, and the tendency of chain-of-thought and retrieval-based agents to accumul…
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…
ToG-Bench: Task-Oriented Spatio-Temporal Grounding in Egocentric Videos
Qi'ao Xu, Tianwen Qian, Yuqian Fu +5
A core capability towards general embodied intelligence lies in localizing task-relevant objects from an egocentric perspective, formulated as Spatio-Temporal Video Grounding (STVG…
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…
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…
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…
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…
OmniGenBench: A Benchmark for Omnipotent Multimodal Generation across 50+ Tasks
Jiayu Wang, Yang Jiao, Yue Yu +4
Recent breakthroughs in large multimodal models (LMMs), such as the impressive GPT-4o-Native, have demonstrated remarkable proficiency in following general-purpose instructions for…
HSACNet: Hierarchical Scale-Aware Consistency Regularized Semi-Supervised Change Detection
Qi'ao Xu, Pengfei Wang, Yanjun Li +2
Semi-supervised change detection (SSCD) aims to detect changes between bi-temporal remote sensing images by utilizing limited labeled data and abundant unlabeled data. Existing met…
NeighborRetr: Balancing Hub Centrality in Cross-Modal Retrieval
Zengrong Lin, Zheng Wang, Tianwen Qian +3
Cross-modal retrieval aims to bridge the semantic gap between different modalities, such as visual and textual data, enabling accurate retrieval across them. Despite significant ad…
Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting
Linhai Zhuo, Zheng Wang, Yuqian Fu +1
The source-free cross-domain few-shot learning (CD-FSL) task aims to transfer pretrained models to target domains utilizing minimal samples, eliminating the need for source domain…
Look Before You Decide: Prompting Active Deduction of MLLMs for Assumptive Reasoning
Yian Li, Wentao Tian, Yang Jiao +5
Recently, Multimodal Large Language Models (MLLMs) have achieved significant success across multiple disciplines due to their exceptional instruction-following capabilities and ext…
NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario
Tianwen Qian, Jingjing Chen, Linhai Zhuo +2
We introduce a novel visual question answering (VQA) task in the context of autonomous driving, aiming to answer natural language questions based on street-view clues. Compared to…
Locate before Answering: Answer Guided Question Localization for Video Question Answering
Tianwen Qian, Ran Cui, Jingjing Chen +3
Video question answering (VideoQA) is an essential task in vision-language understanding, which has attracted numerous research attention recently. Nevertheless, existing works mos…
Video Moment Retrieval from Text Queries via Single Frame Annotation
Ran Cui, Tianwen Qian, Pai Peng +5
Video moment retrieval aims at finding the start and end timestamps of a moment (part of a video) described by a given natural language query. Fully supervised methods need complet…