Search Results for author: Shang-Fu Chen

Found 5 papers, 1 papers with code

Diffusion Model-Augmented Behavioral Cloning

no code implementations26 Feb 2023 Hsiang-Chun Wang, Shang-Fu Chen, Ming-Hao Hsu, Chun-Mao Lai, Shao-Hua Sun

Most existing imitation learning methods that do not require interacting with environments either model the expert distribution as the conditional probability p(a|s) (e. g., behavioral cloning, BC) or the joint probability p(s, a).

Continuous Control Imitation Learning

Learning Facial Liveness Representation for Domain Generalized Face Anti-spoofing

no code implementations16 Aug 2022 Zih-Ching Chen, Lin-Hsi Tsao, Chin-Lun Fu, Shang-Fu Chen, Yu-Chiang Frank Wang

Face anti-spoofing (FAS) aims at distinguishing face spoof attacks from the authentic ones, which is typically approached by learning proper models for performing the associated classification task.

Face Anti-Spoofing

Domain-Generalized Textured Surface Anomaly Detection

no code implementations23 Mar 2022 Shang-Fu Chen, Yu-Min Liu, Chia-Ching Lin, Trista Pei-Chun Chen, Yu-Chiang Frank Wang

By observing normal and abnormal surface data across multiple source domains, our model is expected to be generalized to an unseen textured surface of interest, in which only a small number of normal data can be observed during testing.

Anomaly Detection Domain Generalization +1

Representation Decomposition for Image Manipulation and Beyond

no code implementations2 Nov 2020 Shang-Fu Chen, Jia-Wei Yan, Ya-Fan Su, Yu-Chiang Frank Wang

Representation disentanglement aims at learning interpretable features, so that the output can be recovered or manipulated accordingly.

Attribute Disentanglement +1

Order-Free RNN with Visual Attention for Multi-Label Classification

1 code implementation18 Jul 2017 Shang-Fu Chen, Yi-Chen Chen, Chih-Kuan Yeh, Yu-Chiang Frank Wang

In this paper, we propose the joint learning attention and recurrent neural network (RNN) models for multi-label classification.

Classification General Classification +2

Cannot find the paper you are looking for? You can Submit a new open access paper.