39 citations · 97 across the 9 of their papers we have counts for
7 papers · 1 filter
Semi-Supervised Active Learning with Temporal Output Discrepancy
Siyu Huang, Tianyang Wang, Haoyi Xiong +2
While deep learning succeeds in a wide range of tasks, it highly depends on the massive collection of annotated data which is expensive and time-consuming. To lower the cost of dat…
Generating Person Images with Appearance-aware Pose Stylizer
Siyu Huang, Haoyi Xiong, Zhi-Qi Cheng +5
Generation of high-quality person images is challenging, due to the sophisticated entanglements among image factors, e.g., appearance, pose, foreground, background, local details,…
Ultrafast Photorealistic Style Transfer via Neural Architecture Search
Jie An, Haoyi Xiong, Jun Huan +1
The key challenge in photorealistic style transfer is that an algorithm should faithfully transfer the style of a reference photo to a content photo while the generated image shoul…
Fast Universal Style Transfer for Artistic and Photorealistic Rendering
Jie An, Haoyi Xiong, Jiebo Luo +2
Universal style transfer is an image editing task that renders an input content image using the visual style of arbitrary reference images, including both artistic and photorealist…
StyleNAS: An Empirical Study of Neural Architecture Search to Uncover Surprisingly Fast End-to-End Universal Style Transfer Networks
Jie An, Haoyi Xiong, Jinwen Ma +2
Neural Architecture Search (NAS) has been widely studied for designing discriminative deep learning models such as image classification, object detection, and semantic segmentation…
Data Dropout: Optimizing Training Data for Convolutional Neural Networks
Tianyang Wang, Jun Huan, Bo Li
Deep learning models learn to fit training data while they are highly expected to generalize well to testing data. Most works aim at finding such models by creatively designing arc…