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Tianyu Wang

CUHK

12 papers hereh-index 131.5k citations18 works total

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

author position
  • first author6
  • middle author6

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV12
affiliations
  • CUHK
same name
  • Tianyu Wang — 20 papers, h 9
  • Tianyu Wang — 18 papers, h 7
  • Tianyu Wang — 14 papers
  • Tianyu Wang — 14 papers, h 9
  • Tianyu Wang — 12 papers, h 5
  • Tianyu Wang — 8 papers, h 24

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
20192024
most citedRevisiting Shadow Detection: A New Benchmark Dataset for Complex World

91 citations · 234 across the 12 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019★ 6 cited

Instance Shadow Detection

Tianyu Wang, Xiaowei Hu, Qiong Wang +2

Instance shadow detection is a brand new problem, aiming to find shadow instances paired with object instances. To approach it, we first prepare a new dataset called SOBA, named af…

cs.CV2019★ 91 cited

Revisiting Shadow Detection: A New Benchmark Dataset for Complex World

Xiaowei Hu, Tianyu Wang, Chi-Wing Fu +3

Shadow detection in general photos is a nontrivial problem, due to the complexity of the real world. Though recent shadow detectors have already achieved remarkable performance on…

cs.CV2019★ 15 cited

Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset

Tianyu Wang, Xin Yang, Ke Xu +3

Removing rain streaks from a single image has been drawing considerable attention as rain streaks can severely degrade the image quality and affect the performance of existing outd…

cs.CV2019★ 82 cited

SAC-Net: Spatial Attenuation Context for Salient Object Detection

Xiaowei Hu, Chi-Wing Fu, Lei Zhu +2

This paper presents a new deep neural network design for salient object detection by maximizing the integration of local and global image context within, around, and beyond the sal…

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