127 citations · 140 across the 9 of their papers we have counts for
10 papers
Reference-Efficient Multimodal Bitstream-Corrupted Video Recovery via Depth-Conditioned Adaptation
Tianyi Liu, Jiaojiao Wang, Ye Lu +4
Recovering visually faithful content from damaged video bitstreams is important for reliable multimedia communication and storage. Existing methods exploit local residuals and non-…
FLM: Frequency-Aware Language Models for Generative Image Compression
Jiarun Chen, Kejun Wu, Li Li +3
Generative models have significantly improved the performance ceiling of image lossy compression at low bitrates by exploiting learned priors. However, the generated textures and s…
Making the Invisible Visible: Toward High-Quality Terahertz Tomographic Imaging via Physics-Guided Restoration
Weng-Tai Su, Yi-Chun Hung, Po-Jen Yu +2
Terahertz (THz) tomographic imaging has recently attracted significant attention thanks to its non-invasive, non-destructive, non-ionizing, material-classification, and ultra-fast…
Physics-guided Terahertz Computational Imaging
Weng-Tai Su, Yi-Chun Hung, Po-Jen Yu +2
Visualizing information inside objects is an ever-lasting need to bridge the world from physics, chemistry, biology to computation. Among all tomographic techniques, terahertz (THz…
Keeping Deep Lithography Simulators Updated: Global-Local Shape-Based Novelty Detection and Active Learning
Hao-Chiang Shao, Hsing-Lei Ping, Kuo-shiuan Chen +5
Learning-based pre-simulation (i.e., layout-to-fabrication) models have been proposed to predict the fabrication-induced shape deformation from an IC layout to its fabricated circu…
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation
Bing Li, Yuanlue Zhu, Yitong Wang +3
In this paper, we propose a novel framework to translate a portrait photo-face into an anime appearance. Our aim is to synthesize anime-faces which are style-consistent with a give…
Ensemble Learning with Manifold-Based Data Splitting for Noisy Label Correction
Hao-Chiang Shao, Hsin-Chieh Wang, Weng-Tai Su +1
Label noise in training data can significantly degrade a model's generalization performance for supervised learning tasks. Here we focus on the problem that noisy labels are primar…
Seeing through a Black Box: Toward High-Quality Terahertz TomographicImaging via Multi-Scale Spatio-Spectral Image Fusion
Weng-tai Su, Yi-Chun Hung, Ta-Hsuan Chao +3
Terahertz (THz) imaging has recently attracted significant attention thanks to its non-invasive, non-destructive, non-ionizing, material-classification, and ultra-fast nature for o…
BANet: Blur-aware Attention Networks for Dynamic Scene Deblurring
Fu-Jen Tsai, Yan-Tsung Peng, Yen-Yu Lin +2
Image motion blur results from a combination of object motions and camera shakes, and such blurring effect is generally directional and non-uniform. Previous research attempted to…
DotFAN: A Domain-transferred Face Augmentation Network for Pose and Illumination Invariant Face Recognition
Hao-Chiang Shao, Kang-Yu Liu, Chia-Wen Lin +1
The performance of a convolutional neural network (CNN) based face recognition model largely relies on the richness of labelled training data. Collecting a training set with large…