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Related papers: Underwater Stereo using Refraction-free Image Synt…

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We propose DiffuStereo, a novel system using only sparse cameras (8 in this work) for high-quality 3D human reconstruction. At its core is a novel diffusion-based stereo module, which introduces diffusion models, a type of powerful…

Computer Vision and Pattern Recognition · Computer Science 2022-07-21 Ruizhi Shao , Zerong Zheng , Hongwen Zhang , Jingxiang Sun , Yebin Liu

A solution to the inversion problem of scattering would offer aberration-free diffraction-limited 3D images without the resolution and depth-of-field limitations of lens-based tomographic systems. Powerful algorithms are increasingly being…

Through capturing spatial and angular radiance distribution, light field cameras introduce new capabilities that are not possible with conventional cameras. So far in the light field imaging literature, the focus has been on the theory and…

Computer Vision and Pattern Recognition · Computer Science 2016-11-16 M. Umair Mukati , Bahadir K. Gunturk

Large field-of-view fisheye lens cameras have attracted more and more researchers' attention in the field of robotics. However, there does not exist a convenient off-the-shelf stereo rectification approach which can be applied directly to…

Computer Vision and Pattern Recognition · Computer Science 2017-07-13 Dingfu Zhou , Yuchao Dai , Hongdong Li

Shading-based approaches like Photometric Stereo assume that the image formation model can be effectively optimized for the scene normals. However, in murky water this is a very challenging problem. The light from artificial sources is not…

Computer Vision and Pattern Recognition · Computer Science 2016-05-02 Chourmouzios Tsiotsios , Maria E. Angelopoulou , Andrew J. Davison , Tae-Kyun Kim

We propose a novel framework to automatically learn to aggregate and transform photometric measurements from multiple unstructured views into spatially distinctive and view-invariant low-level features, which are subsequently fed to a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Xiang Feng , Kaizhang Kang , Fan Pei , Huakeng Ding , Jinjiang You , Ping Tan , Kun Zhou , Hongzhi Wu

The demand for stereo images increases as manufacturers launch more XR devices. To meet this demand, we introduce StereoDiffusion, a method that, unlike traditional inpainting pipelines, is trainning free, remarkably straightforward to use,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Lezhong Wang , Jeppe Revall Frisvad , Mark Bo Jensen , Siavash Arjomand Bigdeli

We propose a novel approach that jointly removes reflection or translucent layer from a scene and estimates scene depth. The input data are captured via light field imaging. The problem is couched as minimizing the rank of the transmitted…

Computer Vision and Pattern Recognition · Computer Science 2015-06-16 Qiaosong Wang , Haiting Lin , Yi Ma , Sing Bing Kang , Jingyi Yu

Methods for 3D reconstruction such as Photometric stereo recover the shape and reflectance properties using multiple images of an object taken with variable lighting conditions from a fixed viewpoint. Photometric stereo assumes that a scene…

Computer Vision and Pattern Recognition · Computer Science 2018-11-07 Anish R. Khadka , Paolo Remagnino , Vasileios Argyriou

In this paper, we delve into the realm of 4-D light fields (LFs) to enhance underwater imaging plagued by light absorption, scattering, and other challenges. Contrasting with conventional 2-D RGB imaging, 4-D LF imaging excels in capturing…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Yuji Lin , Junhui Hou , Xianqiang Lyu , Qian Zhao , Deyu Meng

Underwater images are altered by the physical characteristics of the medium through which light rays pass before reaching the optical sensor. Scattering and wavelength-dependent absorption significantly modify the captured colors depending…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Clémentin Boittiaux , Ricard Marxer , Claire Dune , Aurélien Arnaubec , Maxime Ferrera , Vincent Hugel

Capturing the 3D geometry of transparent objects is a challenging task, ill-suited for general-purpose scanning and reconstruction techniques, since these cannot handle specular light transport phenomena. Existing state-of-the-art methods,…

Graphics · Computer Science 2020-09-22 Jiahui Lyu , Bojian Wu , Dani Lischinski , Daniel Cohen-Or , Hui Huang

Despite the increasing prevalence of rotating-style capture (e.g., surveillance cameras), conventional stereo rectification techniques frequently fail due to the rotation-dominant motion and small baseline between views. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Yongcong Zhang , Yifei Xue , Ming Liao , Huiqing Zhang , Yizhen Lao

Non-extractive fish abundance estimation with the aid of visual analysis has drawn increasing attention. Unstable illumination, ubiquitous noise and low frame rate video capturing in the underwater environment, however, make conventional…

Computer Vision and Pattern Recognition · Computer Science 2015-04-16 Meng-Che Chuang , Jenq-Neng Hwang , Kresimir Williams , Richard Towler

This paper shows that accurate underwater 3D shape reconstruction is possible using a single camera, observing a target through a refractive interface. We provide unified reconstruction techniques for a variety of scenarios such as single…

Computer Vision and Pattern Recognition · Computer Science 2019-09-10 Kazuto Ichimaru , Yuichi Taguchi , Hiroshi Kawasaki

Scene depth estimation from stereo and monocular imagery is critical for extracting 3D information for downstream tasks such as scene understanding. Recently, learning-based methods for depth estimation have received much attention due to…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Zhaoshuo Li , Nathan Drenkow , Hao Ding , Andy S. Ding , Alexander Lu , Francis X. Creighton , Russell H. Taylor , Mathias Unberath

Images captured in participating media such as murky water, fog, or smoke are degraded by scattered light. Thus, the use of traditional three-dimensional (3D) reconstruction techniques in such environments is difficult. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2018-04-11 Yuki Fujimura , Masaaki Iiyama , Atsushi Hashimoto , Michihiko Minoh

Active stereo vision is important in reconstructing objects without obvious textures. However, it is still very challenging to extract and match the projected patterns from two camera views automatically and robustly. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2020-04-01 Yongcan Shuang , Zhenzhou Wang

We propose a method for reconstructing a continuous light field of a target scene from a single observed image. Our method takes the best of two worlds: joint aperture-exposure coding for compressive light-field acquisition, and a neural…

Computer Vision and Pattern Recognition · Computer Science 2023-11-17 Yuya Ishikawa , Keita Takahashi , Chihiro Tsutake , Toshiaki Fujii

Neural Radiance Field (NeRF) technology demonstrates immense potential in novel viewpoint synthesis tasks, due to its physics-based volumetric rendering process, which is particularly promising in underwater scenes. Addressing the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-22 Jingchun Zhou , Tianyu Liang , Dehuan Zhang , Zongxin He