1 citations · 4 across the 10 of their papers we have counts for
10 papers
INT-DTT+: Low-Complexity Data-Dependent Transforms for Video Coding
Samuel Fernández-Menduiña, Eduardo Pavez, Antonio Ortega +4
Discrete trigonometric transforms (DTTs), such as the DCT-2 and the DST-7, are widely used in video codecs for their balance between coding performance and computational efficiency…
Leveraging Video Coding Knowledge for Deep Video Enhancement
Thong Bach, Thuong Nguyen Canh, Van-Quang Nguyen
Recent advancements in deep learning techniques have significantly improved the quality of compressed videos. However, previous approaches have not fully exploited the motion chara…
Human-Imperceptible Identification with Learnable Lensless Imaging
Thuong Nguyen Canh, Trung Thanh Ngo, Hajime Nagahara
Lensless imaging protects visual privacy by capturing heavily blurred images that are imperceptible for humans to recognize the subject but contain enough information for machines…
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Meisong Zheng +75
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…
Multi-Scale Deep Compressive Imaging
Thuong Nguyen Canh, Byeungwoo Jeon
Recently, deep learning-based compressive imaging (DCI) has surpassed the conventional compressive imaging in reconstruction quality and faster running time. While multi-scale has…
Restricted Structural Random Matrix for Compressive Sensing
Thuong Nguyen Canh, Byeungwoo Jeon
Compressive sensing (CS) is well-known for its unique functionalities of sensing, compressing, and security (i.e. CS measurements are equally important). However, there is a tradeo…
Error Resilient Deep Compressive Sensing
Thuong, Nguyen Canh, Chien +1
Compressive sensing (CS) is an emerging sampling technology that enables reconstructing signals from a subset of measurements and even corrupted measurements. Deep learning-based c…
Power Control in Cellular Massive MIMO with Varying User Activity: A Deep Learning Solution
Trinh Van Chien, Thuong Nguyen Canh, Emil Björnson +1
This paper considers the sum spectral efficiency (SE) optimization problem in multi-cell Massive MIMO systems with a varying number of active users. This is formulated as a joint p…
Multi-Scale Deep Compressive Sensing Network
Thuong Nguyen Canh, Byeungwoo Jeon
With joint learning of sampling and recovery, the deep learning-based compressive sensing (DCS) has shown significant improvement in performance and running time reduction. Its rec…
Compressive Sensing of Color Images Using Nonlocal Higher Order Dictionary
Khanh Quoc Dinh, Thuong Nguyen Canh, Byeungwoo Jeon
This paper addresses an ill-posed problem of recovering a color image from its compressively sensed measurement data. Differently from the typical 1D vector-based approach of the s…