62 citations · 449 across the 49 of their papers we have counts for
15 papers · 1 filter
Conditional Modeling Based Automatic Video Summarization
Jia-Hong Huang, Chao-Han Huck Yang, Pin-Yu Chen +2
The aim of video summarization is to shorten videos automatically while retaining the key information necessary to convey the overall story. Video summarization methods mainly rely…
Causal Video Summarizer for Video Exploration
Jia-Hong Huang, Chao-Han Huck Yang, Pin-Yu Chen +2
Recently, video summarization has been proposed as a method to help video exploration. However, traditional video summarization models only generate a fixed video summary which is…
Causalainer: Causal Explainer for Automatic Video Summarization
Jia-Hong Huang, Chao-Han Huck Yang, Pin-Yu Chen +2
The goal of video summarization is to automatically shorten videos such that it conveys the overall story without losing relevant information. In many application scenarios, improp…
From 2D Images to 3D Model:Weakly Supervised Multi-View Face Reconstruction with Deep Fusion
Weiguang Zhao, Chaolong Yang, Jianan Ye +6
While weakly supervised multi-view face reconstruction (MVR) is garnering increased attention, one critical issue still remains open: how to effectively interact and fuse multiple…
Treatment Learning Causal Transformer for Noisy Image Classification
Chao-Han Huck Yang, I-Te Danny Hung, Yi-Chieh Liu +1
Current top-notch deep learning (DL) based vision models are primarily based on exploring and exploiting the inherent correlations between training data samples and their associate…
Robust Unsupervised Multi-Object Tracking in Noisy Environments
C. -H. Huck Yang, Mohit Chhabra, Y. -C. Liu +3
Physical processes, camera movement, and unpredictable environmental conditions like the presence of dust can induce noise and artifacts in video feeds. We observe that popular uns…
Longer Version for "Deep Context-Encoding Network for Retinal Image Captioning"
Jia-Hong Huang, Ting-Wei Wu, Chao-Han Huck Yang +1
Automatically generating medical reports for retinal images is one of the promising ways to help ophthalmologists reduce their workload and improve work efficiency. In this work, w…
DeepOpht: Medical Report Generation for Retinal Images via Deep Models and Visual Explanation
Jia-Hong Huang, Chao-Han Huck Yang, Fangyu Liu +9
In this work, we propose an AI-based method that intends to improve the conventional retinal disease treatment procedure and help ophthalmologists increase diagnosis efficiency and…
Wavelet Channel Attention Module with a Fusion Network for Single Image Deraining
Hao-Hsiang Yang, Chao-Han Huck Yang, Yu-Chiang Frank Wang
Single image deraining is a crucial problem because rain severely degenerates the visibility of images and affects the performance of computer vision tasks like outdoor surveillanc…
Y-net: Multi-scale feature aggregation network with wavelet structure similarity loss function for single image dehazing
Hao-Hsiang Yang, Chao-Han Huck Yang, Yi-Chang James Tsai
Single image dehazing is the ill-posed two-dimensional signal reconstruction problem. Recently, deep convolutional neural networks (CNN) have been successfully used in many compute…
Interpretable Self-Attention Temporal Reasoning for Driving Behavior Understanding
Yi-Chieh Liu, Yung-An Hsieh, Min-Hung Chen +3
Performing driving behaviors based on causal reasoning is essential to ensure driving safety. In this work, we investigated how state-of-the-art 3D Convolutional Neural Networks (C…
Synthesizing New Retinal Symptom Images by Multiple Generative Models
Yi-Chieh Liu, Hao-Hsiang Yang, Chao-Han Huck Yang +5
Age-Related Macular Degeneration (AMD) is an asymptomatic retinal disease which may result in loss of vision. There is limited access to high-quality relevant retinal images and po…
When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks
Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen +2
Discovering and exploiting the causality in deep neural networks (DNNs) are crucial challenges for understanding and reasoning causal effects (CE) on an explainable visual model. "…
Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model
C. -H. Huck Yang, Fangyu Liu, Jia-Hong Huang +6
Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. Based on the fact that fun…
A Novel Hybrid Machine Learning Model for Auto-Classification of Retinal Diseases
C. -H. Huck Yang, Jia-Hong Huang, Fangyu Liu +5
Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. We propose a novel visual-…