activity
20192026
most citedSATO: Stable Text-to-Motion Framework

17 citations · 71 across the 42 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

11 papers · 2 filters

cs.CV2024★ 1 cited

Quo Vadis, Anomaly Detection? LLMs and VLMs in the Spotlight

Xi Ding, Lei Wang

Video anomaly detection (VAD) has witnessed significant advancements through the integration of large language models (LLMs) and vision-language models (VLMs), addressing critical…

cs.CV2024★ 8 cited

Do Language Models Understand Time?

Xi Ding, Lei Wang

Large language models (LLMs) have revolutionized video-based computer vision applications, including action recognition, anomaly detection, and video summarization. Videos inherent…

cs.CV2024

When Spatial meets Temporal in Action Recognition

Huilin Chen, Lei Wang, Yifan Chen +2

Video action recognition has made significant strides, but challenges remain in effectively using both spatial and temporal information. While existing methods often focus on eithe…

cs.CV2024★ 2 cited

Learnable Expansion of Graph Operators for Multi-Modal Feature Fusion

Dexuan Ding, Lei Wang, Liyun Zhu +2

In computer vision tasks, features often come from diverse representations, domains (e.g., indoor and outdoor), and modalities (e.g., text, images, and videos). Effectively fusing…

cs.CV2024

TrackNetV4: Enhancing Fast Sports Object Tracking with Motion Attention Maps

Arjun Raj, Lei Wang, Tom Gedeon

Accurately detecting and tracking high-speed, small objects, such as balls in sports videos, is challenging due to factors like motion blur and occlusion. Although recent deep lear…

cs.CV2024★ 2 cited

Motion meets Attention: Video Motion Prompts

Qixiang Chen, Lei Wang, Piotr Koniusz +1

Videos contain rich spatio-temporal information. Traditional methods for extracting motion, used in tasks such as action recognition, often rely on visual contents rather than prec…