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K. Cheng

15 papers hereh-index 5916k citations523 works total

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

author position
  • first author2
  • middle author7
  • last author5

Across the 14 of 15 papers where every author was matched, so the position is known.

fields
  • cs.CV8
  • cs.LG3
  • cs.ET1
  • cs.PF1
  • cs.RO1
  • eess.IV1
same name
  • K. Cheng — 81 papers, h 46
  • K. Cheng — 23 papers, h 10
  • K. Cheng — 12 papers, h 6
  • K. Cheng — 12 papers, h 34
  • K. Cheng — 9 papers, h 3
  • K. Cheng — 6 papers, h 15

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 citedBi-Modality Medical Image Synthesis Using Semi-Supervised Sequential Generative Adversarial Networks

72 citations · 86 across the 8 of their papers we have counts for

collaborators
Showing 2019 · cs.CVShow all

4 papers · 2 filters

cs.CV2019

Facial age estimation by deep residual decision making

Shichao Li, Kwang-Ting Cheng

Residual representation learning simplifies the optimization problem of learning complex functions and has been widely used by traditional convolutional neural networks. However, i…

cs.CV2019

Multi-Frame Content Integration with a Spatio-Temporal Attention Mechanism for Person Video Motion Transfer

Kun Cheng, Hao-Zhi Huang, Chun Yuan +2

Existing person video generation methods either lack the flexibility in controlling both the appearance and motion, or fail to preserve detailed appearance and temporal consistency…

cs.CV2019★ 4 cited

Visualizing the decision-making process in deep neural decision forest

Shichao Li, Kwang-Ting Cheng

Deep neural decision forest (NDF) achieved remarkable performance on various vision tasks via combining decision tree and deep representation learning. In this work, we first trace…

cs.CV2019

MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning

Zechun Liu, Haoyuan Mu, Xiangyu Zhang +4

In this paper, we propose a novel meta learning approach for automatic channel pruning of very deep neural networks. We first train a PruningNet, a kind of meta network, which is a…

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