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20172022
most citedCAFE-GAN: Arbitrary Face Attribute Editing with Complementary Attention Feature

18 citations · 52 across the 10 of their papers we have counts for

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cs.CV2022

3d human motion generation from the text via gesture action classification and the autoregressive model

Gwantae Kim, Youngsuk Ryu, Junyeop Lee +3

In this paper, a deep learning-based model for 3D human motion generation from the text is proposed via gesture action classification and an autoregressive model. The model focuses…

cs.CV20221 cited

Controllable Face Manipulation and UV Map Generation by Self-supervised Learning

Yuanming Li, Jeong-gi Kwak, David Han +1

Although manipulating facial attributes by Generative Adversarial Networks (GANs) has been remarkably successful recently, there are still some challenges in explicit control of fe…

cs.CV2021

Memory-based Semantic Segmentation for Off-road Unstructured Natural Environments

Youngsaeng Jin, David K. Han, Hanseok Ko

With the availability of many datasets tailored for autonomous driving in real-world urban scenes, semantic segmentation for urban driving scenes achieves significant progress. How…

cs.CV20211 cited

CPNet: Cross-Parallel Network for Efficient Anomaly Detection

Youngsaeng Jin, Jonghwan Hong, David Han +1

Anomaly detection in video streams is a challenging problem because of the scarcity of abnormal events and the difficulty of accurately annotating them. To alleviate these issues,…

cs.CV202018 cited

CAFE-GAN: Arbitrary Face Attribute Editing with Complementary Attention Feature

Jeong-gi Kwak, David K. Han, Hanseok Ko

The goal of face attribute editing is altering a facial image according to given target attributes such as hair color, mustache, gender, etc. It belongs to the image-to-image domai…