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Kexue Fu

12 papers hereh-index 13875 citations28 works total

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

author position
  • first author4
  • middle author6

Across the 10 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV11
  • cs.RO1
same name
  • Kexue Fu — 7 papers, h 5
  • Kexue Fu — 7 papers, h 3
  • Kexue Fu — 4 papers, h 2
  • Kexue Fu — 4 papers, h 6

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
20212023
most citedRobust Point Cloud Registration Framework Based on Deep Graph Matching(TPAMI Version)

49 citations · 157 across the 12 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022★ 49 cited

Robust Point Cloud Registration Framework Based on Deep Graph Matching(TPAMI Version)

Kexue Fu, Jiazheng Luo, Xiaoyuan Luo +3

3D point cloud registration is a fundamental problem in computer vision and robotics. Recently, learning-based point cloud registration methods have made great progress. However, t…

cs.CV2022★ 1 cited

Boosting Point-BERT by Multi-choice Tokens

Kexue Fu, Mingzhi Yuan, Manning Wang

Masked language modeling (MLM) has become one of the most successful self-supervised pre-training task. Inspired by its success, Point-BERT, as a pioneer work in point cloud, propo…

cs.CV2022★ 3 cited

POS-BERT: Point Cloud One-Stage BERT Pre-Training

Kexue Fu, Peng Gao, ShaoLei Liu +3

Recently, the pre-training paradigm combining Transformer and masked language modeling has achieved tremendous success in NLP, images, and point clouds, such as BERT. However, dire…

cs.CV2022★ 13 cited

Distillation with Contrast is All You Need for Self-Supervised Point Cloud Representation Learning

Kexue Fu, Peng Gao, Renrui Zhang +3

In this paper, we propose a simple and general framework for self-supervised point cloud representation learning. Human beings understand the 3D world by extracting two levels of i…

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