3 citations · 4 across the 6 of their papers we have counts for
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cs.CV2025
RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation
Jing Hu, Chengming Feng, Shu Hu +4
Arbitrary style transfer aims to apply the style of any given artistic image to another content image. Still, existing deep learning-based methods often require significant computa…
cs.CV2024★ 1 cited
Efficient Image Super-Resolution via Symmetric Visual Attention Network
Chengxu Wu, Qinrui Fan, Shu Hu +3
An important development direction in the Single-Image Super-Resolution (SISR) algorithms is to improve the efficiency of the algorithms. Recently, efficient Super-Resolution (SR)…
cs.CV2023★ 3 cited
RL-I2IT: Image-to-Image Translation with Deep Reinforcement Learning
Jing Hu, Ziwei Luo, Chengming Feng +7
Most existing Image-to-Image Translation (I2IT) methods generate images in a single run of a deep learning (DL) model. However, designing such a single-step model is always challen…