activity
20192022
most citedA Comprehensive Study of Deep Video Action Recognition

115 citations · 155 across the 14 of their papers we have counts for

collaborators

22 papers

cs.CV2022

Large Scale Real-World Multi-Person Tracking

Bing Shuai, Alessandro Bergamo, Uta Buechler +3

This paper presents a new large scale multi-person tracking dataset -- \texttt{PersonPath22}, which is over an order of magnitude larger than currently available high quality multi…

cs.CV20221 cited

An In-depth Study of Stochastic Backpropagation

Jun Fang, Mingze Xu, Hao Chen +3

In this paper, we provide an in-depth study of Stochastic Backpropagation (SBP) when training deep neural networks for standard image classification and object detection tasks. Dur…

cs.CV20221 cited

What to look at and where: Semantic and Spatial Refined Transformer for detecting human-object interactions

A S M Iftekhar, Hao Chen, Kaustav Kundu +3

We propose a novel one-stage Transformer-based semantic and spatial refined transformer (SSRT) to solve the Human-Object Interaction detection task, which requires to localize huma…

cs.CV2022

SCVRL: Shuffled Contrastive Video Representation Learning

Michael Dorkenwald, Fanyi Xiao, Biagio Brattoli +2

We propose SCVRL, a novel contrastive-based framework for self-supervised learning for videos. Differently from previous contrast learning based methods that mostly focus on learni…

cs.CV20221 cited

Hierarchical Self-supervised Representation Learning for Movie Understanding

Fanyi Xiao, Kaustav Kundu, Joseph Tighe +1

Most self-supervised video representation learning approaches focus on action recognition. In contrast, in this paper we focus on self-supervised video learning for movie understan…

cs.CV20222 cited

Transfer of Representations to Video Label Propagation: Implementation Factors Matter

Daniel McKee, Zitong Zhan, Bing Shuai +3

This work studies feature representations for dense label propagation in video, with a focus on recently proposed methods that learn video correspondence using self-supervised sign…