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Underwater scene reconstruction is a critical tech-nology for underwater operations, enabling the generation of 3D models from images captured by underwater platforms. However, the quality of underwater images is often degraded due to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Junhao Shi , Jisheng Xu , Jianping He , Zhiliang Lin

Significant attention has been attracted to deep learning-based depth estimates. Dynamic objects become the most hard problems in inter-frame-supervised depth estimates due to the uncertainty in adjacent frames. Thus, integrating optical…

Computer Vision and Pattern Recognition · Computer Science 2023-10-04 Zhengyang Lu , Ying Chen

We propose a method to interactively control the animation of fluid elements in still images to generate cinemagraphs. Specifically, we focus on the animation of fluid elements like water, smoke, fire, which have the properties of repeating…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Aniruddha Mahapatra , Kuldeep Kulkarni

In moving camera videos, motion segmentation is commonly performed using the image plane motion of pixels, or optical flow. However, objects that are at different depths from the camera can exhibit different optical flows even if they share…

Computer Vision and Pattern Recognition · Computer Science 2015-11-06 Manjunath Narayana , Allen Hanson , Erik Learned-Miller

Particle Imaging Velocimetry (PIV) estimates the flow of fluid by analyzing the motion of injected particles. The problem is challenging as the particles lie at different depths but have similar appearance and tracking a large number of…

Computer Vision and Pattern Recognition · Computer Science 2020-03-24 Zhong Li , Jinwei Ye , Yu Ji , Hao Sheng , Jingyi Yu

Event cameras capture brightness changes asynchronously with microsecond resolution, yet existing optical flow methods fail to fully exploit this temporal continuity. Frame-based approaches impose artificial accumulation latency and suffer…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Gunwoo Jeon , Chaesong Park , Jongwoo Lim

The paper proposes a method to secure the Compressive Sensing (CS) streams. It consists in protecting part of the measurements by a secret key and inserting the code into the rest. The secret key is generated via a cryptographically secure…

Cryptography and Security · Computer Science 2025-05-30 Cristina-Elena Popa , Cristian Damian , Daniela Coltuc

Diffusion models (DMs) have demonstrated remarkable success in real-world image super-resolution (SR), yet their reliance on time-consuming multi-step sampling largely hinders their practical applications. While recent efforts have…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jiaqi Xu , Wenbo Li , Haoze Sun , Fan Li , Zhixin Wang , Long Peng , Jingjing Ren , Haoran Yang , Xiaowei Hu , Renjing Pei , Pheng-Ann Heng

Modeling the mechanics of fluid in complex scenes is vital to applications in design, graphics, and robotics. Learning-based methods provide fast and differentiable fluid simulators, however most prior work is unable to accurately model how…

Machine Learning · Computer Science 2023-09-12 Arjun Mani , Ishaan Preetam Chandratreya , Elliot Creager , Carl Vondrick , Richard Zemel

In this paper, we consider the task of unsupervised object discovery in videos. Previous works have shown promising results via processing optical flows to segment objects. However, taking flow as input brings about two drawbacks. First,…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Shuangrui Ding , Weidi Xie , Yabo Chen , Rui Qian , Xiaopeng Zhang , Hongkai Xiong , Qi Tian

Snapshot compressed sensing (CS) refers to compressive imaging systems in which multiple frames are mapped into a single measurement frame. Each pixel in the acquired frame is a noisy linear mapping of the corresponding pixels in the frames…

Information Theory · Computer Science 2019-04-30 Shirin Jalali , Xin Yuan

Due to the complex interplay of light absorption and scattering in the underwater environment, underwater images experience significant degradation. This research presents a two-stage underwater image enhancement network called the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Han Mei , Kunqian Li , Shuaixin Liu , Chengzhi Ma , Qianli Jiang

Single-pixel cameras based on the concepts of compressed sensing (CS) leverage the inherent structure of images to retrieve them with far fewer measurements and operate efficiently over a significantly broader spectral range than…

Computer Vision and Pattern Recognition · Computer Science 2016-06-17 Qiang Guo , Hongwei Chen , Yuxi Wang , Yong Guo , Peng Liu , Xiurui Zhu , Zheng Cheng , Zhenming Yu , Minghua Chen , Sigang Yang , Shizhong Xie

Reconstructing dynamic, time-varying scenes with computed tomography (4D-CT) is a challenging and ill-posed problem common to industrial and medical settings. Existing 4D-CT reconstructions are designed for sparse sampling schemes that…

Image and Video Processing · Electrical Eng. & Systems 2021-04-26 Albert W. Reed , Hyojin Kim , Rushil Anirudh , K. Aditya Mohan , Kyle Champley , Jingu Kang , Suren Jayasuriya

Reconstructing and tracking dynamic 3D scenes remains a fundamental challenge in computer vision. Existing approaches often decouple geometry from motion: multi-view reconstruction methods assume static scenes, while dynamic tracking…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Shenhan Qian , Ganlin Zhang , Shangzhe Wu , Daniel Cremers

A common distortion in videos is image instability in the form of chaotic (global and local displacements). Those instabilities can be used to enhance image resolution by using subpixel elastic registration. In this work, we investigate the…

Optics · Physics 2013-02-28 Gil Shabat

Direct numerical simulation (DNS) of turbulent flows is computationally expensive and cannot be applied to flows with large Reynolds numbers. Large eddy simulation (LES) is an alternative that is computationally less demanding, but is…

Fluid Dynamics · Physics 2021-09-09 Shengyu Chen , Shervin Sammak , Peyman Givi , Joseph P. Yurko1 , Xiaowei Jia

Event cameras capture changes of illumination in the observed scene rather than accumulating light to create images. Thus, they allow for applications under high-speed motion and complex lighting conditions, where traditional framebased…

Computer Vision and Pattern Recognition · Computer Science 2021-12-21 Vincent Brebion , Julien Moreau , Franck Davoine

Spatial multiplexing cameras (SMCs) acquire a (typically static) scene through a series of coded projections using a spatial light modulator (e.g., a digital micro-mirror device) and a few optical sensors. This approach finds use in imaging…

Computer Vision and Pattern Recognition · Computer Science 2015-08-06 Aswin C. Sankaranarayanan , Lina Xu , Christoph Studer , Yun Li , Kevin Kelly , Richard G. Baraniuk

Small-scale features of shallow water flow obtained from direct numerical simulation (DNS) with two different computational codes for the shallow water equations are gathered offline and subsequently employed with the aim of constructing a…

Fluid Dynamics · Physics 2022-02-24 Sagy Ephrati , Erwin Luesink , Golo Wimmer , Paolo Cifani , Bernard Geurts