55 citations · 67 across the 11 of their papers we have counts for
11 papers
Light Field Depth Estimation via Stitched Epipolar Plane Images
Ping Zhou, Langqing Shi, Xiaoyang Liu +3
Depth estimation is a fundamental problem in light field processing. Epipolar-plane image (EPI)-based methods often encounter challenges such as low accuracy in slope computation d…
Content-aware Warping for View Synthesis
Mantang Guo, Junhui Hou, Jing Jin +3
Existing image-based rendering methods usually adopt depth-based image warping operation to synthesize novel views. In this paper, we reason the essential limitations of the tradit…
Learning Dynamic Interpolation for Extremely Sparse Light Fields with Wide Baselines
Mantang Guo, Jing Jin, Hui Liu +1
In this paper, we tackle the problem of dense light field (LF) reconstruction from sparsely-sampled ones with wide baselines and propose a learnable model, namely dynamic interpola…
Occlusion-aware Unsupervised Learning of Depth from 4-D Light Fields
Jing Jin, Junhui Hou
Depth estimation is a fundamental issue in 4-D light field processing and analysis. Although recent supervised learning-based light field depth estimation methods have significantl…
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…
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…
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…
Light Field Spatial Super-resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization
Jing Jin, Junhui Hou, Jie Chen +1
Light field (LF) images acquired by hand-held devices usually suffer from low spatial resolution as the limited sampling resources have to be shared with the angular dimension. LF…
Learning Light Field Angular Super-Resolution via a Geometry-Aware Network
Jing Jin, Junhui Hou, Hui Yuan +1
The acquisition of light field images with high angular resolution is costly. Although many methods have been proposed to improve the angular resolution of a sparsely-sampled light…
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…
Light Field Super-resolution via Attention-Guided Fusion of Hybrid Lenses
Jing Jin, Junhui Hou, Jie Chen +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…