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Jianfei Cai

11 papers hereh-index 111.1k citations20 works total

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

author position
  • middle author3
  • last author8

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • eess.IV2
same name
  • Jianfei Cai — 91 papers, h 69
  • Jianfei Cai — 26 papers, h 19
  • Jianfei Cai — 15 papers, h 9
  • Jianfei Cai — 10 papers, h 8
  • Jianfei Cai — 8 papers, h 3
  • Jianfei Cai — 8 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
20212025
most citedSem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields

30 citations · 57 across the 11 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022★ 5 cited

Dual Adaptive Transformations for Weakly Supervised Point Cloud Segmentation

Zhonghua Wu, Yicheng Wu, Guosheng Lin +2

Weakly supervised point cloud segmentation, i.e. semantically segmenting a point cloud with only a few labeled points in the whole 3D scene, is highly desirable due to the heavy bu…

cs.CV2022★ 6 cited

Image Captioning In the Transformer Age

Yang Xu, Li Li, Haiyang Xu +3

Image Captioning (IC) has achieved astonishing developments by incorporating various techniques into the CNN-RNN encoder-decoder architecture. However, since CNN and RNN do not sha…

cs.CV2022★ 30 cited

Sem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields

Yuedong Chen, Qianyi Wu, Chuanxia Zheng +2

Image translation and manipulation have gain increasing attention along with the rapid development of deep generative models. Although existing approaches have brought impressive r…

eess.IV2022★ 2 cited

Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation

Yicheng Wu, Zhonghua Wu, Qianyi Wu +2

Semi-supervised segmentation remains challenging in medical imaging since the amount of annotated medical data is often scarce and there are many blurred pixels near the adhesive e…

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