activity
20212026
most citedTowards Efficient Convolutional Network Models with Filter Distribution Templates

2 citations · 4 across the 3 of their papers we have counts for

collaborators

10 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

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

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

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.CV2022

SuperTran: Reference Based Video Transformer for Enhancing Low Bitrate Streams in Real Time

Tejas Khot, Nataliya Shapovalova, Silviu Andrei +1

This work focuses on low bitrate video streaming scenarios (e.g. 50 - 200Kbps) where the video quality is severely compromised. We present a family of novel deep generative models…