activity
20242026
collaborators

7 papers

cs.CV2026

SpatialMem: Metric-Aligned Long-Horizon Video Memory for Language Grounding and QA

Xinyi Zheng, Yunze Liu, Chi-Hao Wu +5

We present SpatialMem, a memory-centric system for long-horizon, language-grounded retrieval and QA from egocentric video, where metric 3D serves as an interpretable indexing scaff…

cs.CV2025

From Detection to Anticipation: Online Understanding of Struggles across Various Tasks and Activities

Shijia Feng, Michael Wray, Walterio Mayol-Cuevas

Understanding human skill performance is essential for intelligent assistive systems, with struggle recognition offering a natural cue for identifying user difficulties. While prio…

cs.CV2025

X-LeBench: A Benchmark for Extremely Long Egocentric Video Understanding

Wenqi Zhou, Kai Cao, Hao Zheng +8

Long-form egocentric video understanding provides rich contextual information and unique insights into long-term human behaviors, holding significant potential for applications in…

cs.CV2025

CULTURE3D: A Large-Scale and Diverse Dataset of Cultural Landmarks and Terrains for Gaussian-Based Scene Rendering

Xinyi Zheng, Steve Zhang, Weizhe Lin +4

Current state-of-the-art 3D reconstruction models face limitations in building extra-large scale outdoor scenes, primarily due to the lack of sufficiently large-scale and detailed…

cs.CV2025

EvoStruggle: A Dataset Capturing the Evolution of Struggle across Activities and Skill Levels

Shijia Feng, Michael Wray, Walterio Mayol-Cuevas

The ability to determine when a person struggles during skill acquisition is crucial for both optimizing human learning and enabling the development of effective assistive systems.…

cs.CV2025

Are you Struggling? Dataset and Baselines for Struggle Determination in Assembly Videos

Shijia Feng, Michael Wray, Brian Sullivan +4

Determining when people are struggling allows for a finer-grained understanding of actions that complements conventional action classification and error detection. Struggle detecti…