activity
20172022
most citedSingle Shot Temporal Action Detection

380 citations · 739 across the 5 of their papers we have counts for

collaborators

12 papers

cs.CV20221 cited

An Efficient COarse-to-fiNE Alignment Framework @ Ego4D Natural Language Queries Challenge 2022

Zhijian Hou, Wanjun Zhong, Lei Ji +6

This technical report describes the CONE approach for Ego4D Natural Language Queries (NLQ) Challenge in ECCV 2022. We leverage our model CONE, an efficient window-centric COarse-to…

cs.CV2021

Searching for Two-Stream Models in Multivariate Space for Video Recognition

Xinyu Gong, Heng Wang, Zheng Shou +3

Conventional video models rely on a single stream to capture the complex spatial-temporal features. Recent work on two-stream video models, such as SlowFast network and AssembleNet…

cs.CV2020

Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization

Junting Pan, Siyu Chen, Mike Zheng Shou +3

Localizing persons and recognizing their actions from videos is a challenging task towards high-level video understanding. Recent advances have been achieved by modeling direct pai…

cs.CV2020

SF-Net: Single-Frame Supervision for Temporal Action Localization

Fan Ma, Linchao Zhu, Yi Yang +4

In this paper, we study an intermediate form of supervision, i.e., single-frame supervision, for temporal action localization (TAL). To obtain the single-frame supervision, the ann…

cs.CV2019

Towards Train-Test Consistency for Semi-supervised Temporal Action Localization

Xudong Lin, Zheng Shou, Shih-Fu Chang

Recently, Weakly-supervised Temporal Action Localization (WTAL) has been densely studied but there is still a large gap between weakly-supervised models and fully-supervised models…

cs.LG2019

CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation

Jiawei Ma, Zheng Shou, Alireza Zareian +3

Many real-world applications involve multivariate, geo-tagged time series data: at each location, multiple sensors record corresponding measurements. For example, air quality monit…