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Yulan Guo

9 papers hereh-index 113.7k citations17 works total

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

author position
  • middle author4
  • last author5

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CV9
same name
  • Yulan Guo — 32 papers, h 24
  • Yulan Guo — 8 papers, h 20
  • Yulan Guo — 6 papers, h 3
  • Yulan Guo — 6 papers, h 4
  • Yulan Guo — 6 papers, h 5
  • Yulan Guo — 6 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
20192022
most citedLearning Semantic Segmentation of Large-Scale Point Clouds with Random Sampling

224 citations · 420 across the 7 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022

4DAC: Learning Attribute Compression for Dynamic Point Clouds

Guangchi Fang, Qingyong Hu, Yiling Xu +1

With the development of the 3D data acquisition facilities, the increasing scale of acquired 3D point clouds poses a challenge to the existing data compression techniques. Although…

cs.CV2022★ 19 cited

Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds

Yifan Zhang, Qingyong Hu, Guoquan Xu +3

We study the problem of efficient object detection of 3D LiDAR point clouds. To reduce the memory and computational cost, existing point-based pipelines usually adopt task-agnostic…

cs.CV2022

3DAC: Learning Attribute Compression for Point Clouds

Guangchi Fang, Qingyong Hu, Hanyun Wang +2

We study the problem of attribute compression for large-scale unstructured 3D point clouds. Through an in-depth exploration of the relationships between different encoding steps an…

cs.CV2022★ 6 cited

Box2Seg: Learning Semantics of 3D Point Clouds with Box-Level Supervision

Yan Liu, Qingyong Hu, Yinjie Lei +3

Learning dense point-wise semantics from unstructured 3D point clouds with fewer labels, although a realistic problem, has been under-explored in literature. While existing weakly…

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