87 citations · 131 across the 22 of their papers we have counts for
5 papers · 1 filter
Learning Priors for Adversarial Autoencoders
Hui-Po Wang, Wen-Hsiao Peng, Wei-Jan Ko
Most deep latent factor models choose simple priors for simplicity, tractability or not knowing what prior to use. Recent studies show that the choice of the prior may have a profo…
Learning Goal-Oriented Visual Dialog Agents: Imitating and Surpassing Analytic Experts
Yen-Wei Chang, Wen-Hsiao Peng
This paper tackles the problem of learning a questioner in the goal-oriented visual dialog task. Several previous works adopt model-free reinforcement learning. Most pretrain the m…
Learned Image Compression with Soft Bit-based Rate-Distortion Optimization
David Alexandre, Chih-Peng Chang, Wen-Hsiao Peng +1
This paper introduces the notion of soft bits to address the rate-distortion optimization for learning-based image compression. Recent methods for such compression train an autoenc…
All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation
Wei-Lun Chang, Hui-Po Wang, Wen-Hsiao Peng +1
In this paper we tackle the problem of unsupervised domain adaptation for the task of semantic segmentation, where we attempt to transfer the knowledge learned upon synthetic datas…
An Autoencoder-based Learned Image Compressor: Description of Challenge Proposal by NCTU
David Alexandre, Chih-Peng Chang, Wen-Hsiao Peng +1
We propose a lossy image compression system using the deep-learning autoencoder structure to participate in the Challenge on Learned Image Compression (CLIC) 2018. Our autoencoder…