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Pingping Zhang

34 papers hereh-index 355.4k citations60 works total

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

author position
  • first author8
  • middle author20
  • last author2

Across the 30 of 34 papers where every author was matched, so the position is known.

fields
  • cs.CV29
  • cs.GR3
  • cs.CL1
  • stat.ML1
same name
  • Pingping Zhang — 19 papers, h 11
  • Pingping Zhang — 9 papers, h 4
  • Pingping Zhang — 8 papers, h 5
  • Pingping Zhang — 4 papers, h 2
  • Pingping Zhang — 4 papers, h 4
  • Pingping Zhang — 3 papers, h 2

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
20172023
most citedAmulet: Aggregating Multi-level Convolutional Features for Salient Object Detection

116 citations · 294 across the 21 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CV2020

Hierarchical Paired Channel Fusion Network for Street Scene Change Detection

Yinjie Lei, Duo Peng, Pingping Zhang +2

Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging ta…

cs.CV2020★ 5 cited

Semi-Supervised Crowd Counting via Self-Training on Surrogate Tasks

Yan Liu, Lingqiao Liu, Peng Wang +2

Most existing crowd counting systems rely on the availability of the object location annotation which can be expensive to obtain. To reduce the annotation cost, one attractive solu…

cs.GR2020

Real-time Image Smoothing via Iterative Least Squares

Wei Liu, Pingping Zhang, Xiaolin Huang +3

Edge-preserving image smoothing is a fundamental procedure for many computer vision and graphic applications. There is a tradeoff between the smoothing quality and the processing s…

cs.CV2020★ 7 cited

Towards Using Count-level Weak Supervision for Crowd Counting

Yinjie Lei, Yan Liu, Pingping Zhang +1

Most existing crowd counting methods require object location-level annotation, i.e., placing a dot at the center of an object. While being simpler than the bounding-box or pixel-le…

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