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Ping Tan

24 papers hereh-index 201.9k citations29 works total

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

author position
  • middle author5
  • last author18

Across the 23 of 24 papers where every author was matched, so the position is known.

fields
  • cs.CV22
  • cs.GR1
  • cs.RO1
same name
  • Ping Tan — 17 papers, h 9
  • Ping Tan — 8 papers, h 5
  • Ping Tan — 8 papers, h 4
  • Ping Tan — 7 papers, h 1
  • Ping Tan — 7 papers, h 5
  • Ping Tan — 5 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
20182023
most citedQuadTree Attention for Vision Transformers

70 citations · 254 across the 24 of their papers we have counts for

collaborators
Showing 2021 · cs.CVShow all

4 papers · 2 filters

cs.CV2021★ 3 cited

GB-CosFace: Rethinking Softmax-based Face Recognition from the Perspective of Open Set Classification

Lizhe Liu, Mingqiang Chen, Xiaohao Chen +2

State-of-the-art face recognition methods typically take the multi-classification pipeline and adopt the softmax-based loss for optimization. Although these methods have achieved g…

cs.CV2021

FloorPlanCAD: A Large-Scale CAD Drawing Dataset for Panoptic Symbol Spotting

Zhiwen Fan, Lingjie Zhu, Honghua Li +3

Access to large and diverse computer-aided design (CAD) drawings is critical for developing symbol spotting algorithms. In this paper, we present FloorPlanCAD, a large-scale real-w…

cs.CV2021★ 16 cited

CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

Lizhe Liu, Xiaohao Chen, Siyu Zhu +1

Modern deep-learning-based lane detection methods are successful in most scenarios but struggling for lane lines with complex topologies. In this work, we propose CondLaneNet, a no…

cs.CV2021★ 2 cited

DRO: Deep Recurrent Optimizer for Video to Depth

Xiaodong Gu, Weihao Yuan, Zuozhuo Dai +4

There are increasing interests of studying the video-to-depth (V2D) problem with machine learning techniques. While earlier methods directly learn a mapping from images to depth ma…

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