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Rao Fu

5 papers hereh-index 41.3k citations9 works total

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

author position
  • first author1
  • middle author2

Across the 3 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • eess.IV1
same name
  • Rao Fu — 15 papers, h 9
  • Rao Fu — 6 papers
  • Rao Fu — 1 paper
  • Rao Fu — 1 paper, h 4
  • Rao Fu — 1 paper
  • Rao Fu — 1 paper, 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

most citedMedical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

223 citations · 385 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023★ 1 cited

Patch-Wise Point Cloud Generation: A Divide-and-Conquer Approach

Cheng Wen, Baosheng Yu, Rao Fu +1

A generative model for high-fidelity point clouds is of great importance in synthesizing 3d environments for applications such as autonomous driving and robotics. Despite the recen…

cs.CV2023★ 6 cited

BPNet: Bézier Primitive Segmentation on 3D Point Clouds

Rao Fu, Cheng Wen, Qian Li +2

This paper proposes BPNet, a novel end-to-end deep learning framework to learn Bézier primitive segmentation on 3D point clouds. The existing works treat different primitive types…

cs.CV2023★ 223 cited

Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Junde Wu, Wei Ji, Yuanpei Liu +4

The Segment Anything Model (SAM) has recently gained popularity in the field of image segmentation due to its impressive capabilities in various segmentation tasks and its prompt-b…

cs.CV2022★ 140 cited

MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model

Junde Wu, Rao Fu, Huihui Fang +5

Diffusion probabilistic model (DPM) recently becomes one of the hottest topic in computer vision. Its image generation application such as Imagen, Latent Diffusion Models and Stabl…

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