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researcher

Lin Shao

14 papers hereh-index 181.1k citations27 works total

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

author position
  • first author5
  • middle author8
  • last author1

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.RO8
  • cs.CV4
  • cs.LG2
same name
  • Lin Shao — 8 papers, h 4
  • Lin Shao — 8 papers, h 3
  • Lin Shao — 4 papers, h 3
  • Lin Shao — 4 papers, h 3
  • Lin Shao — 3 papers, h 3
  • Lin Shao — 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 citedLarge-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

53 citations · 61 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023★ 3 cited

Category-Level Multi-Part Multi-Joint 3D Shape Assembly

Yichen Li, Kaichun Mo, Yueqi Duan +5

Shape assembly composes complex shapes geometries by arranging simple part geometries and has wide applications in autonomous robotic assembly and CAD modeling. Existing works focu…

cs.CV2020

Generative 3D Part Assembly via Dynamic Graph Learning

Jialei Huang, Guanqi Zhan, Qingnan Fan +5

Autonomous part assembly is a challenging yet crucial task in 3D computer vision and robotics. Analogous to buying an IKEA furniture, given a set of 3D parts that can assemble a si…

cs.CV2020

Learning 3D Part Assembly from a Single Image

Yichen Li, Kaichun Mo, Lin Shao +2

Autonomous assembly is a crucial capability for robots in many applications. For this task, several problems such as obstacle avoidance, motion planning, and actuator control have…

cs.CV2017★ 53 cited

Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

Li Yi, Lin Shao, Manolis Savva +47

We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks: part-level segmentation…

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