Results 11 to 20 of about 15,737,282 (353)
MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Video [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 The past few years have witnessed great success in applying deep learning to enhance the quality of compressed image/video. The existing approaches mainly focus on enhancing the quality of a single frame, not considering the similarity between ...
Guan, Zhenyu +5 more
core +2 more sources
A CNN-Based Prediction-Aware Quality Enhancement Framework for VVC [PDF]
IEEE Open Journal of Signal Processing, 2021 This paper presents a framework for Convolutional Neural Network (CNN)-based quality enhancement task, by taking advantage of coding information in the compressed video signal.
Fatemeh Nasiri +4 more
doaj +2 more sources
Multi-Frame Quality Enhancement for Compressed Video [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 The past few years have witnessed great success in applying deep learning to enhance the quality of compressed image/video. The existing approaches mainly focus on enhancing the quality of a single frame, ignoring the similarity between consecutive ...
Li, Tianyi +3 more
core +2 more sources
GQE-Net: A Graph-Based Quality Enhancement Network for Point Cloud Color Attribute [PDF]
IEEE Transactions on Image Processing, 2023 In recent years, point clouds have become increasingly popular for representing three-dimensional (3D) visual objects and scenes. To efficiently store and transmit point clouds, compression methods have been developed, but they often result in a ...
Jinrui Xing +4 more
semanticscholar +1 more source
Fast-MFQE: A Fast Approach for Multi-Frame Quality Enhancement on Compressed Video. [PDF]
Sensors (Basel), 2023 For compressed images and videos, quality enhancement is essential. Though there have been remarkable achievements related to deep learning, deep learning models are too large to apply to real-time tasks. Therefore, a fast multi-frame quality enhancement
Chen K, Chen J, Zeng H, Shen X.
europepmc +2 more sources
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results [PDF]
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 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 LDV dataset (240 videos) and 95 additional videos. This challenge includes
Ren Yang +76 more
semanticscholar +1 more source
End-to-End Transformer for Compressed Video Quality Enhancement [PDF]
IEEE transactions on broadcasting, 2022 Convolutional neural networks have achieved excellent results in compressed video quality enhancement task in recent years. State-of-the-art methods explore the spatio-temporal information of adjacent frames mainly by deformable convolution. However, the
Li Yu +3 more
semanticscholar +1 more source
NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with focus on proposed solutions and results. In this challenge, the new Large-scale Diverse Video (LDV) dataset is employed. The challenge has three tracks.
Ren Yang +71 more
semanticscholar +1 more source
IEEE Systems Journal, 2021 This article investigates the power quality enhancement of a grid-tied photovoltaic (PV) distribution system by employing a fuzzy logic proportional–integrator–derivative multiple complex coefficient filter multiple second-order generalized integrator ...
N. Babu P +4 more
semanticscholar +1 more source
NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Dataset and Study [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 This paper introduces a novel dataset for video enhancement and studies the state-of-the-art methods of the NTIRE 2021 challenge on quality enhancement of com-pressed video.
Ren Yang, Radu Timofte, Xin Li
semanticscholar +1 more source