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Chang Tang

4 papers hereh-index 121k citations16 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Chang Tang — 6 papers, h 4
  • Chang Tang — 4 papers, h 34
  • Chang Tang — 4 papers, h 6
  • Chang Tang — 3 papers, h 4
  • Chang Tang — 3 papers, h 14
  • Chang Tang — 2 papers, h 13

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152020
most citedDeep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences

36 citations · 47 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2020★ 1 cited

Unsupervised Domain Expansion from Multiple Sources

Jing Zhang, Wanqing Li, Lu sheng +2

Given an existing system learned from previous source domains, it is desirable to adapt the system to new domains without accessing and forgetting all the previous domains in some…

cs.CV2016★ 7 cited

RGB-D-based Action Recognition Datasets: A Survey

Jing Zhang, Wanqing Li, Philip O. Ogunbona +2

Human action recognition from RGB-D (Red, Green, Blue and Depth) data has attracted increasing attention since the first work reported in 2010. Over this period, many benchmark dat…

cs.CV2015★ 3 cited

Online Action Recognition based on Incremental Learning of Weighted Covariance Descriptors

Chang Tang, Pichao Wang, Wanqing Li

Different from traditional action recognition based on video segments, online action recognition aims to recognize actions from unsegmented streams of data in a continuous manner.…

cs.CV2015★ 36 cited

Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences

Pichao Wang, Wanqing Li, Zhimin Gao +3

Recently, deep learning approach has achieved promising results in various fields of computer vision. In this paper, a new framework called Hierarchical Depth Motion Maps (HDMM) +…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.