Journal ArticleDOI
Resolution Enhancement in Multi-Image Stereo
Arnav Bhavsar,A. N. Rajagopalan +1 more
TLDR
This paper proposes an integrated approach to estimate the HR depth and the SR image from multiple LR stereo observations and demonstrates the efficacy of the proposed method in not only being able to bring out image details but also in enhancing theHR depth over its LR counterpart.Abstract:
Under stereo settings, the twin problems of image superresolution (SR) and high-resolution (HR) depth estimation are intertwined. The subpixel registration information required for image superresolution is tightly coupled to the 3D structure. The effects of parallax and pixel averaging (inherent in the downsampling process) preclude a priori estimation of pixel motion for superresolution. These factors also compound the correspondence problem at low resolution (LR), which in turn affects the quality of the LR depth estimates. In this paper, we propose an integrated approach to estimate the HR depth and the SR image from multiple LR stereo observations. Our results demonstrate the efficacy of the proposed method in not only being able to bring out image details but also in enhancing the HR depth over its LR counterpart.read more
Citations
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Proceedings ArticleDOI
SwiniPASSR: Swin Transformer based Parallax Attention Network for Stereo Image Super-Resolution
TL;DR: This paper proposes a novel approach namely SwiniPASSR, which adopts Swin Transformer as the backbone, meanwhile incorporating it with the Bi-directional Parallax Attention Module (biPAM) to maximize auxiliary information given by the binocular mechanism.
Proceedings ArticleDOI
Simultaneously Estimation of Super-Resolution Images and Depth Maps from Low Resolution Sensors
TL;DR: This work proposes a method that combines depth fusion and image reconstruction in a super-resolution framework that creates new images and depth maps of higher resolution and minimizes issues related with the absence of information in the depth map.
Journal ArticleDOI
Parallax-based second-order mixed attention for stereo image super-resolution
Chenyang Duan,Nanfeng Xiao +1 more
Proceedings ArticleDOI
A New Dataset and Transformer for Stereoscopic Video Super-Resolution
TL;DR: Trans-SVSR as mentioned in this paper proposes a novel Transformer-based model for stereo video super-resolution, which comprises two key novel components: a spatio-temporal convolutional self-attention layer and an optical flow-based feed-forward layer that discovers the correlation across different video frames and aligns the features.
Dissertation
Appearance Modelling for 4D Representations
TL;DR: A view-independent, high resolution appearance representation is proposed that successfully encodes the high visual variability of objects under various movements and is cast the appearance modelling as a dimensionality reduction problem.
References
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Proceedings ArticleDOI
Computing visual correspondence with occlusions using graph cuts
Vladimir Kolmogorov,Ramin Zabih +1 more
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Book
Markov Random Field Modeling in Computer Vision
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