activity
20212023
most citedSoccerNet 2022 Challenges Results

37 citations · 48 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023

E2E-LOAD: End-to-End Long-form Online Action Detection

Shuqiang Cao, Weixin Luo, Bairui Wang +2

Recently, there has been a growing trend toward feature-based approaches for Online Action Detection (OAD). However, these approaches have limitations due to their fixed backbone d…

cs.CV2022★ 37 cited

SoccerNet 2022 Challenges Results

Silvio Giancola, Anthony Cioppa, Adrien Deliège +91

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks:…

cs.CV2022★ 4 cited

Learning Point-Language Hierarchical Alignment for 3D Visual Grounding

Jiaming Chen, Weixin Luo, Ran Song +3

This paper presents a novel hierarchical alignment model (HAM) that learns multi-granularity visual and linguistic representations in an end-to-end manner. We extract key points an…

cs.CV2022

Provably Uncertainty-Guided Universal Domain Adaptation

Yifan Wang, Lin Zhang, Ran Song +3

Universal domain adaptation (UniDA) aims to transfer the knowledge from a labeled source domain to an unlabeled target domain without any assumptions of the label sets, which requi…

cs.CV2022★ 2 cited

A Circular Window-based Cascade Transformer for Online Action Detection

Shuqiang Cao, Weixin Luo, Bairui Wang +2

Online action detection aims at the accurate action prediction of the current frame based on long historical observations. Meanwhile, it demands real-time inference on online strea…

cs.CV2022

Exploiting Inter-Sample Affinity for Knowability-Aware Universal Domain Adaptation

Yifan Wang, Lin Zhang, Ran Song +3

Universal domain adaptation (UniDA) aims to transfer the knowledge of common classes from the source domain to the target domain without any prior knowledge on the label set, which…

eess.SP2021★ 5 cited

Sensoring and Application of Multimodal Data for the Detection of Freezing of Gait in Parkinson's Disease

Wei Zhang, Debin Huang, Hantao Li +7

The accurate and reliable detection or prediction of freezing of gaits (FOG) is important for fall prevention in Parkinson's Disease (PD) and studying the physiological transitions…