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Hong Zhang

4 papers here

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

author position
  • first author2
  • middle author1
  • last author1

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

fields
  • cs.CV3
  • cs.RO1
same name
  • Hong Zhang — 8 papers, h 59
  • Hong Zhang — 7 papers, h 23
  • Hong Zhang — 6 papers, h 15
  • Hong Zhang — 6 papers, h 6
  • Hong Zhang — 5 papers, h 10
  • Hong Zhang — 5 papers

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

most citedMonoDistill: Learning Spatial Features for Monocular 3D Object Detection

59 citations · 60 across the 4 of their papers we have counts for

collaborators

4 papers

cs.RO2022

Following Closely: A Robust Monocular Person Following System for Mobile Robot

Hanjing Ye, Jieting Zhao, Yaling Pan +2

Monocular person following (MPF) is a capability that supports many useful applications of a mobile robot. However, existing MPF solutions are not completely satisfactory. Firstly,…

cs.CV2022★ 59 cited

MonoDistill: Learning Spatial Features for Monocular 3D Object Detection

Zhiyu Chong, Xinzhu Ma, Hong Zhang +4

3D object detection is a fundamental and challenging task for 3D scene understanding, and the monocular-based methods can serve as an economical alternative to the stereo-based or…

cs.CV2020

Full Matching on Low Resolution for Disparity Estimation

Hong Zhang, Shenglun Chen, Zhihui Wang +2

A Multistage Full Matching disparity estimation scheme (MFM) is proposed in this work. We demonstrate that decouple all similarity scores directly from the low-resolution 4D volume…

cs.CV2020★ 1 cited

Direct Depth Learning Network for Stereo Matching

Hong Zhang, Haojie Li, Shenglun Chen +4

Being a crucial task of autonomous driving, Stereo matching has made great progress in recent years. Existing stereo matching methods estimate disparity instead of depth. They trea…

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