176 citations · 333 across the 12 of their papers we have counts for
12 papers
TransRef: Multi-Scale Reference Embedding Transformer for Reference-Guided Image Inpainting
Taorong Liu, Liang Liao, Delin Chen +4
Image inpainting for completing complicated semantic environments and diverse hole patterns of corrupted images is challenging even for state-of-the-art learning-based inpainting m…
Local-Global Temporal Difference Learning for Satellite Video Super-Resolution
Yi Xiao, Qiangqiang Yuan, Kui Jiang +4
Optical-flow-based and kernel-based approaches have been extensively explored for temporal compensation in satellite Video Super-Resolution (VSR). However, these techniques are les…
Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label Diffusion
Liang Liao, Wenyi Chen, Jing Xiao +3
Understanding foggy image sequence in the driving scenes is critical for autonomous driving, but it remains a challenging task due to the difficulty in collecting and annotating re…
Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest Filters
Mingbao Lin, Liujuan Cao, Yuxin Zhang +3
This paper focuses on filter-level network pruning. A novel pruning method, termed CLR-RNF, is proposed. We first reveal a "long-tail" long-tail pruning problem in magnitude-based…
Information Competing Process for Learning Diversified Representations
Jie Hu, Rongrong Ji, ShengChuan Zhang +4
Learning representations with diversified information remains as an open problem. Towards learning diversified representations, a new approach, termed Information Competing Process…
How to Write High-quality News on Social Network? Predicting News Quality by Mining Writing Style
Yuting Yang, Juan Cao, Mingyan Lu +2
Rapid development of Internet technologies promotes traditional newspapers to report news on social networks. However, people on social networks may have different needs which natu…
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination
Chih-Chung Hsu, Chia-Wen Lin, Weng-Tai Su +1
Despite generative adversarial networks (GANs) can hallucinate photo-realistic high-resolution (HR) faces from low-resolution (LR) faces, they cannot guarantee preserving the ident…
CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data
Chih-Chung Hsu, Chia-Wen Lin
Given a large unlabeled set of images, how to efficiently and effectively group them into clusters based on extracted visual representations remains a challenging problem. To addre…
TFDASH: A Fairness, Stability, and Efficiency Aware Rate Control Approach for Multiple Clients over DASH
Chao Zhou, Chia-Wen Lin, Xinggong Zhang +1
Dynamic adaptive streaming over HTTP (DASH) has recently been widely deployed in the Internet and adopted in the industry. It, however, does not impose any adaptation logic for sel…
Graph-based Joint Signal / Power Restoration for Energy Harvesting Wireless Sensor Networks
Megumi Kaneko, Gene Cheung, Weng-tai Su +1
The design of energy and spectrally efficient Wireless Sensor Networks (WSN) is crucial to support the upcoming expansion of IoT/M2M mobile data traffic. In this work, we consider…
Graph Fourier Transform with Negative Edges for Depth Image Coding
Weng-Tai Su, Gene Cheung, Chia-Wen Lin
Recent advent in graph signal processing (GSP) has led to the development of new graph-based transforms and wavelets for image / video coding, where the underlying graph describes…
Robust Semi-Supervised Graph Classifier Learning with Negative Edge Weights
Gene Cheung, Weng-Tai Su, Yu Mao +1
In a semi-supervised learning scenario, (possibly noisy) partially observed labels are used as input to train a classifier, in order to assign labels to unclassified samples. In th…