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Probabilistic-based Feature Embedding of 4-D Light Fields for Compressive Imaging and Denoising
Xianqiang Lyu, Junhui Hou
The high-dimensional nature of the 4-D light field (LF) poses great challenges in achieving efficient and effective feature embedding, that severely impacts the performance of down…
GQE-Net: A Graph-based Quality Enhancement Network for Point Cloud Color Attribute
Jinrui Xing, Hui Yuan, Raouf Hamzaoui +2
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, co…
Rank-Enhanced Low-Dimensional Convolution Set for Hyperspectral Image Denoising
Jinhui Hou, Zhiyu Zhu, Hui Liu +1
This paper tackles the challenging problem of hyperspectral (HS) image denoising. Unlike existing deep learning-based methods usually adopting complicated network architectures or…
Deep Amended Gradient Descent for Efficient Spectral Reconstruction from Single RGB Images
Zhiyu Zhu, Hui Liu, Junhui Hou +2
This paper investigates the problem of recovering hyperspectral (HS) images from single RGB images. To tackle such a severely ill-posed problem, we propose a physically-interpretab…
Attention-Guided Progressive Neural Texture Fusion for High Dynamic Range Image Restoration
Jie Chen, Zaifeng Yang, Tsz Nam Chan +3
High Dynamic Range (HDR) imaging via multi-exposure fusion is an important task for most modern imaging platforms. In spite of recent developments in both hardware and algorithm in…
Light Field Reconstruction via Deep Adaptive Fusion of Hybrid Lenses
Jing Jin, Mantang Guo, Junhui Hou +2
This paper explores the problem of reconstructing high-resolution light field (LF) images from hybrid lenses, including a high-resolution camera surrounded by multiple low-resoluti…
Reduced Reference Perceptual Quality Model and Application to Rate Control for 3D Point Cloud Compression
Qi Liu, Hui Yuan, Raouf Hamzaoui +3
In rate-distortion optimization, the encoder settings are determined by maximizing a reconstruction quality measure subject to a constraint on the bit rate. One of the main challen…
Deep Selective Combinatorial Embedding and Consistency Regularization for Light Field Super-resolution
Jing Jin, Junhui Hou, Zhiyu Zhu +2
Light field (LF) images acquired by hand-held devices usually suffer from low spatial resolution as the limited detector resolution has to be shared with the angular dimension. LF…
Subjective Quality Database and Objective Study of Compressed Point Clouds With 6DoF Head-Mounted Display
Xinju Wu, Yun Zhang, Chunling Fan +2
In this paper, we focus on subjective and objective Point Cloud Quality Assessment (PCQA) in an immersive environment and study the effect of geometry and texture attributes in com…
Deep Spatial-angular Regularization for Compressive Light Field Reconstruction over Coded Apertures
Mantang Guo, Junhui Hou, Jing Jin +2
Coded aperture is a promising approach for capturing the 4-D light field (LF), in which the 4-D data are compressively modulated into 2-D coded measurements that are further decode…
Hyperspectral Image Super-resolution via Deep Progressive Zero-centric Residual Learning
Zhiyu Zhu, Junhui Hou, Jie Chen +2
This paper explores the problem of hyperspectral image (HSI) super-resolution that merges a low resolution HSI (LR-HSI) and a high resolution multispectral image (HR-MSI). The cros…
NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image
Boaz Arad, Radu Timofte, Ohad Ben-Shahar +4
This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. As…
Model-based Joint Bit Allocation between Geometry and Color for Video-based 3D Point Cloud Compression
Qi Liu, Hui Yuan, Junhui Hou +2
Rate distortion optimization plays a very important role in image/video coding. But for 3D point cloud, this problem has not been investigated. In this paper, the rate and distorti…
A Comprehensive Study and Comparison of Core Technologies for MPEG 3D Point Cloud Compression
Hao Liu, Hui Yuan, Qi Liu +2
Point cloud based 3D visual representation is becoming popular due to its ability to exhibit the real world in a more comprehensive and immersive way. However, under a limited netw…
Deep Coarse-to-fine Dense Light Field Reconstruction with Flexible Sampling and Geometry-aware Fusion
Jing Jin, Junhui Hou, Jie Chen +3
A densely-sampled light field (LF) is highly desirable in various applications, such as 3-D reconstruction, post-capture refocusing and virtual reality. However, it is costly to ac…