activity
20182020
most citedComplex Sequential Understanding through the Awareness of Spatial and Temporal Concepts

27 citations · 51 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV20208 cited

ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation

Hanwen Cao, Yongyi Lu, Cewu Lu +3

Recent works of point clouds show that mulit-frame spatio-temporal modeling outperforms single-frame versions by utilizing cross-frame information. In this paper, we further improv…

eess.IV2020

NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results

Dario Fuoli, Zhiwu Huang, Martin Danelljan +18

This paper reviews the NTIRE 2020 challenge on video quality mapping (VQM), which addresses the issues of quality mapping from source video domain to target video domain. The chall…

cs.CV202010 cited

TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model

Bo Pang, Yizhuo Li, Yifan Zhang +2

Multi-object tracking is a fundamental vision problem that has been studied for a long time. As deep learning brings excellent performances to object detection algorithms, Tracking…

cs.CV202027 cited

Complex Sequential Understanding through the Awareness of Spatial and Temporal Concepts

Bo Pang, Kaiwen Zha, Hanwen Cao +3

Understanding sequential information is a fundamental task for artificial intelligence. Current neural networks attempt to learn spatial and temporal information as a whole, limite…

cs.CV20206 cited

Asynchronous Interaction Aggregation for Action Detection

Jiajun Tang, Jin Xia, Xinzhi Mu +2

Understanding interaction is an essential part of video action detection. We propose the Asynchronous Interaction Aggregation network (AIA) that leverages different interactions to…

cs.CV2019

Three Branches: Detecting Actions With Richer Features

Jin Xia, Jiajun Tang, Cewu Lu

We present our three branch solutions for International Challenge on Activity Recognition at CVPR2019. This model seeks to fuse richer information of global video clip, short human…