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Gim Hee Lee

National University of Singapore

40 papers hereh-index 439.1k citations81 works total

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

author position
  • middle author6
  • last author33

Across the 39 of 40 papers where every author was matched, so the position is known.

fields
  • cs.CV35
  • cs.RO4
  • cs.LG1
affiliations
  • National University of Singapore
Homepage
same name
  • Gim Hee Lee — 22 papers, h 11
  • Gim Hee Lee — 17 papers, h 5
  • Gim Hee Lee — 13 papers, h 7
  • Gim Hee Lee — 10 papers, h 3
  • Gim Hee Lee — 6 papers, h 4
  • Gim Hee Lee — 6 papers, h 4

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 citedRPM-Net: Robust Point Matching using Learned Features

624 citations · 1.4k across the 39 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CV2023★ 2 cited

Towards Robust Few-shot Point Cloud Semantic Segmentation

Yating Xu, Na Zhao, Gim Hee Lee

Few-shot point cloud semantic segmentation aims to train a model to quickly adapt to new unseen classes with only a handful of support set samples. However, the noise-free assumpti…

cs.CV2023

Generalized Few-Shot Point Cloud Segmentation Via Geometric Words

Yating Xu, Conghui Hu, Na Zhao +1

Existing fully-supervised point cloud segmentation methods suffer in the dynamic testing environment with emerging new classes. Few-shot point cloud segmentation algorithms address…

cs.CV2023

Robust e-NeRF: NeRF from Sparse & Noisy Events under Non-Uniform Motion

Weng Fei Low, Gim Hee Lee

Event cameras offer many advantages over standard cameras due to their distinctive principle of operation: low power, low latency, high temporal resolution and high dynamic range.…

cs.CV2023★ 2 cited

Weakly-supervised 3D Pose Transfer with Keypoints

Jinnan Chen, Chen Li, Gim Hee Lee

The main challenges of 3D pose transfer are: 1) Lack of paired training data with different characters performing the same pose; 2) Disentangling pose and shape information from th…

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