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Lu Fang

4 papers hereh-index 343 citations4 works total

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

author position
  • middle author2
  • last author2

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

fields
  • cs.CV4
same name
  • Lu Fang — 23 papers, h 28
  • Lu Fang — 4 papers, h 17
  • Lu Fang — 4 papers, h 3
  • Lu Fang — 4 papers, h 3
  • Lu Fang — 3 papers
  • Lu Fang — 3 papers, h 3

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 citedLEAD: LiDAR Extender for Autonomous Driving

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

collaborators

4 papers

cs.CV2023

SVQNet: Sparse Voxel-Adjacent Query Network for 4D Spatio-Temporal LiDAR Semantic Segmentation

Xuechao Chen, Shuangjie Xu, Xiaoyi Zou +3

LiDAR-based semantic perception tasks are critical yet challenging for autonomous driving. Due to the motion of objects and static/dynamic occlusion, temporal information plays an…

cs.CV2023

ClickSeg: 3D Instance Segmentation with Click-Level Weak Annotations

Leyao Liu, Tao Kong, Minzhao Zhu +2

3D instance segmentation methods often require fully-annotated dense labels for training, which are costly to obtain. In this paper, we present ClickSeg, a novel click-level weakly…

cs.CV2023★ 2 cited

Crowd3D: Towards Hundreds of People Reconstruction from a Single Image

Hao Wen, Jing Huang, Huili Cui +4

Image-based multi-person reconstruction in wide-field large scenes is critical for crowd analysis and security alert. However, existing methods cannot deal with large scenes contai…

cs.CV2021★ 2 cited

LEAD: LiDAR Extender for Autonomous Driving

Jianing Zhang, Wei Li, Honggang Gou +2

3D perception using sensors under vehicle industrial standard is the rigid demand in autonomous driving. MEMS LiDAR emerges with irresistible trend due to its lower cost, more robu…

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