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Jie Cao

26 papers hereh-index 216.7k citations42 works total

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

author position
  • first author7
  • middle author19

Across the 26 of 26 papers where every author was matched, so the position is known.

fields
  • cs.CV20
  • cs.LG3
  • cs.SD1
  • cs.SI1
  • eess.IV1
same name
  • Jie Cao — 16 papers, h 2
  • Jie Cao — 12 papers, h 19
  • Jie Cao — 12 papers, h 9
  • Jie Cao — 9 papers, h 3
  • Jie Cao — 8 papers, h 22
  • Jie Cao — 7 papers, h 3

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 citedLocalViT: Analyzing Locality in Vision Transformers

285 citations · 670 across the 26 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CV2020

P2 Net: Augmented Parallel-Pyramid Net for Attention Guided Pose Estimation

Luanxuan Hou, Jie Cao, Yuan Zhao +3

We propose an augmented Parallel-Pyramid Net (P2 Net) with feature refinement by dilated bottleneck and attention module. During data preprocessing, we proposed a differentiable…

cs.CV2020★ 5 cited

Reference-guided Face Component Editing

Qiyao Deng, Jie Cao, Yunfan Liu +3

Face portrait editing has achieved great progress in recent years. However, previous methods either 1) operate on pre-defined face attributes, lacking the flexibility of controllin…

cs.CV2020★ 4 cited

Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation

Luanxuan Hou, Jie Cao, Yuan Zhao +4

The target of human pose estimation is to determine body part or joint locations of each person from an image. This is a challenging problems with wide applications. To address thi…

cs.CV2020★ 1 cited

Informative Sample Mining Network for Multi-Domain Image-to-Image Translation

Jie Cao, Huaibo Huang, Yi Li +2

The performance of multi-domain image-to-image translation has been significantly improved by recent progress in deep generative models. Existing approaches can use a unified model…

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