86 citations · 89 across the 5 of their papers we have counts for
6 papers
SASMU: boost the performance of generalized recognition model using synthetic face dataset
Chia-Chun Chung, Pei-Chun Chang, Yong-Sheng Chen +2
Nowadays, deploying a robust face recognition product becomes easy with the development of face recognition techniques for decades. Not only profile image verification but also the…
Self-Supervised Robustifying Guidance for Monocular 3D Face Reconstruction
Hitika Tiwari, Min-Hung Chen, Yi-Min Tsai +5
Despite the recent developments in 3D Face Reconstruction from occluded and noisy face images, the performance is still unsatisfactory. Moreover, most existing methods rely on addi…
MS-SincResNet: Joint learning of 1D and 2D kernels using multi-scale SincNet and ResNet for music genre classification
Pei-Chun Chang, Yong-Sheng Chen, Chang-Hsing Lee
In this study, we proposed a new end-to-end convolutional neural network, called MS-SincResNet, for music genre classification. MS-SincResNet appends 1D multi-scale SincNet (MS-Sin…
Learning Facial Representations from the Cycle-consistency of Face
Jia-Ren Chang, Yong-Sheng Chen, Wei-Chen Chiu
Faces manifest large variations in many aspects, such as identity, expression, pose, and face styling. Therefore, it is a great challenge to disentangle and extract these character…
Deep Competitive Pathway Networks
Jia-Ren Chang, Yong-Sheng Chen
In the design of deep neural architectures, recent studies have demonstrated the benefits of grouping subnetworks into a larger network. For examples, the Inception architecture in…
Batch-normalized Maxout Network in Network
Jia-Ren Chang, Yong-Sheng Chen
This paper reports a novel deep architecture referred to as Maxout network In Network (MIN), which can enhance model discriminability and facilitate the process of information abst…