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R. Jiang

11 papers hereh-index 13405 citations29 works total

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

author position
  • middle author10
  • last author1

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

fields
  • cs.CV11
same name
  • R. Jiang — 37 papers, h 47
  • R. Jiang — 10 papers, h 8
  • R. Jiang — 9 papers, h 10
  • R. Jiang — 8 papers, h 19
  • R. Jiang — 5 papers, h 6
  • R. Jiang — 5 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
20212026
most citedContinuous Face Aging via Self-estimated Residual Age Embedding

2 citations · 5 across the 11 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CV2021

Semantic Relation Preserving Knowledge Distillation for Image-to-Image Translation

Zeqi Li, Ruowei Jiang, Parham Aarabi

Generative adversarial networks (GANs) have shown significant potential in modeling high dimensional distributions of image data, especially on image-to-image translation tasks. Ho…

cs.CV2021★ 1 cited

Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example

Robin Kips, Ruowei Jiang, Sileye Ba +5

While makeup virtual-try-on is now widespread, parametrizing a computer graphics rendering engine for synthesizing images of a given cosmetics product remains a challenging task. I…

cs.CV2021★ 2 cited

Continuous Face Aging via Self-estimated Residual Age Embedding

Zeqi Li, Ruowei Jiang, Parham Aarabi

Face synthesis, including face aging, in particular, has been one of the major topics that witnessed a substantial improvement in image fidelity by using generative adversarial net…

cs.CV2021

The GIST and RIST of Iterative Self-Training for Semi-Supervised Segmentation

Eu Wern Teh, Terrance DeVries, Brendan Duke +3

We consider the task of semi-supervised semantic segmentation, where we aim to produce pixel-wise semantic object masks given only a small number of human-labeled training examples…

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