2 code implementations • ECCV 2020 • Yun-Zhu Song, Zhi Rui Tam, Hung-Jen Chen, Huiao-Han Lu, Hong-Han Shuai
Different from video generation that focuses on maintaining the continuity of generated images (frames), story visualization emphasizes preserving the global consistency of characters and scenes across different story pictures, which is very challenging since story sentences only provide sparse signals for generating images.
Ranked #2 on Story Visualization on Pororo (using extra training data)
no code implementations • ICCV 2023 • HongXia Xie, Ming-Xian Lee, Tzu-Jui Chen, Hung-Jen Chen, Hou-I Liu, Hong-Han Shuai, Wen-Huang Cheng
Then, the Cross-Patch Attention module is proposed to fuse the features of MIP and global context together to complement each other.
1 code implementation • 29 Dec 2021 • Hitika Tiwari, Min-Hung Chen, Yi-Min Tsai, Hsien-Kai Kuo, Hung-Jen Chen, Kevin Jou, K. S. Venkatesh, Yong-Sheng Chen
Therefore, we propose a Self-Supervised RObustifying GUidancE (ROGUE) framework to obtain robustness against occlusions and noise in the face images.
no code implementations • 22 Apr 2021 • Min-Fong Hong, Hao-Yun Chen, Min-Hung Chen, Yu-Syuan Xu, Hsien-Kai Kuo, Yi-Min Tsai, Hung-Jen Chen, Kevin Jou
We propose an NSS method to directly search for efficient-aware network spaces automatically, reducing the manual effort and immense cost in discovering satisfactory ones.
no code implementations • NeurIPS 2020 • Hung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun
To preserve the knowledge we learn from previous instances, we proposed a method to protect the path by restricting the gradient updates of one instance from overriding past updates calculated from previous instances if these instances are not similar.
2 code implementations • 27 Apr 2020 • Cheng-Ming Chiang, Yu Tseng, Yu-Syuan Xu, Hsien-Kai Kuo, Yi-Min Tsai, Guan-Yu Chen, Koan-Sin Tan, Wei-Ting Wang, Yu-Chieh Lin, Shou-Yao Roy Tseng, Wei-Shiang Lin, Chia-Lin Yu, BY Shen, Kloze Kao, Chia-Ming Cheng, Hung-Jen Chen
To the best of our knowledge, this is the first paper that addresses all the deployment issues of image deblurring task across mobile devices.
no code implementations • CVPR 2019 • Hung-Jen Chen, Ka-Ming Hui, Szu-Yu Wang, Li-Wu Tsao, Hong-Han Shuai, Wen-Huang Cheng
To facilitate on-demand makeup transfer, in this work, we propose BeautyGlow that decompose the latent vectors of face images derived from the Glow model into makeup and non-makeup latent vectors.