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In this work, we address the problem of jointly estimating albedo, normals, depth and 3D spatially-varying lighting from a single image. Most existing methods formulate the task as image-to-image translation, ignoring the 3D properties of…

Computer Vision and Pattern Recognition · Computer Science 2021-10-22 Zian Wang , Jonah Philion , Sanja Fidler , Jan Kautz

This paper presents novel techniques for recovering 3D dense scene flow, based on differential analysis of 4D light fields. The key enabling result is a per-ray linear equation, called the ray flow equation, that relates 3D scene flow to 4D…

Computer Vision and Pattern Recognition · Computer Science 2019-09-24 Sizhuo Ma , Brandon M. Smith , Mohit Gupta

Representing scenes from multi-view images is a crucial task in computer vision with extensive applications. However, inherent photometric distortions in the camera imaging can significantly degrade image quality. Without accounting for…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Weichen Dai , Kangcheng Ma , Jiaxin Wang , Kecen Pan , Yuhang Ming , Hua Zhang , Wanzeng Kong

We propose a modular framework for single-view indoor scene 3D reconstruction, where several core modules are powered by diffusion techniques. Traditional approaches for this task often struggle with the complex instance shapes and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Yuxiao Li

We introduce GeMS, a framework for 3D Gaussian Splatting (3DGS) designed to handle severely motion-blurred images. State-of-the-art deblurring methods for extreme blur, such as ExBluRF, as well as Gaussian Splatting-based approaches like…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Gopi Raju Matta , Trisha Reddypalli , Vemunuri Divya Madhuri , Kaushik Mitra

Omnidirectional 3D Gaussian Splatting with panoramas is a key technique for 3D scene representation, and existing methods typically rely on slow SfM to provide camera poses and sparse points priors. In this work, we propose a pose-free…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Chuanqing Zhuang , Xin Lu , Zehui Deng , Zhengda Lu , Yiqun Wang , Junqi Diao , Jun Xiao

Low-light image enhancement remains a challenging task, particularly in the absence of paired training data. In this study, we present LucentVisionNet, a novel zero-shot learning framework that addresses the limitations of traditional and…

Image and Video Processing · Electrical Eng. & Systems 2025-06-25 Muhammad Azeem Aslam , Hassan Khalid , Nisar Ahmed

The problem of identifying the 3D pose of a known object from a given 2D image has important applications in Computer Vision. Our proposed method of registering a 3D model of a known object on a given 2D photo of the object has numerous…

Computer Vision and Pattern Recognition · Computer Science 2013-12-02 Srimal Jayawardena , Marcus Hutter , Nathan Brewer

Mask-based lensless cameras can be flat, thin, and light-weight, which makes them suitable for novel designs of computational imaging systems with large surface areas and arbitrary shapes. Despite recent progress in lensless cameras, the…

Image and Video Processing · Electrical Eng. & Systems 2023-01-11 Yucheng Zheng , M. Salman Asif

We present a lightweight solution to recover 3D pose from multi-view images captured with spatially calibrated cameras. Building upon recent advances in interpretable representation learning, we exploit 3D geometry to fuse input images into…

Computer Vision and Pattern Recognition · Computer Science 2020-06-23 Edoardo Remelli , Shangchen Han , Sina Honari , Pascal Fua , Robert Wang

Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision. This paper presents a solution to the problem of 3D…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Yi Zhou , Guillermo Gallego , Henri Rebecq , Laurent Kneip , Hongdong Li , Davide Scaramuzza

Decompositional reconstruction of 3D scenes, with complete shapes and detailed texture of all objects within, is intriguing for downstream applications but remains challenging, particularly with sparse views as input. Recent approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Junfeng Ni , Yu Liu , Ruijie Lu , Zirui Zhou , Song-Chun Zhu , Yixin Chen , Siyuan Huang

Event-based structured light systems have recently been introduced as an exciting alternative to conventional frame-based triangulation systems for the 3D measurements of diffuse surfaces. Important benefits include the fast capture speed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Aniket Dashpute , Jiazhang Wang , James Taylor , Oliver Cossairt , Ashok Veeraraghavan , Florian Willomitzer

Recovering textures under shadows has remained a challenging problem due to the difficulty of inferring shadow-free scenes from shadow images. In this paper, we propose the use of diffusion models as they offer a promising approach to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Kangfu Mei , Luis Figueroa , Zhe Lin , Zhihong Ding , Scott Cohen , Vishal M. Patel

We tackle the problem of automatically reconstructing a complete 3D model of a scene from a single RGB image. This challenging task requires inferring the shape of both visible and occluded surfaces. Our approach utilizes viewer-centered,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-28 Daeyun Shin , Zhile Ren , Erik B. Sudderth , Charless C. Fowlkes

3D Gaussian Splatting (3DGS) has demonstrated remarkable real-time performance in novel view synthesis, yet its effectiveness relies heavily on dense multi-view inputs with precisely known camera poses, which are rarely available in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zongqi He , Hanmin Li , Kin-Chung Chan , Yushen Zuo , Hao Xie , Zhe Xiao , Jun Xiao , Kin-Man Lam

In this paper, we propose an approach to address the problem of 3D reconstruction of scenes from a single image captured by a light-field camera equipped with a rolling shutter sensor. Our method leverages the 3D information cues present in…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Hermes McGriff , Renato Martins , Nicolas Andreff , Cédric Demonceaux

3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the quality of reconstructions depends heavily on high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yiren Lu , Yunlai Zhou , Disheng Liu , Tuo Liang , Yu Yin

We propose FD3, a fundus image enhancement method based on direct diffusion bridges, which can cope with a wide range of complex degradations, including haze, blur, noise, and shadow. We first propose a synthetic forward model through a…

Image and Video Processing · Electrical Eng. & Systems 2024-09-20 Sehui Kim , Hyungjin Chung , Se Hie Park , Eui-Sang Chung , Kayoung Yi , Jong Chul Ye

Nighttime photography encounters escalating challenges in extremely low-light conditions, primarily attributable to the ultra-low signal-to-noise ratio. For real-world deployment, a practical solution must not only produce visually…

Computer Vision and Pattern Recognition · Computer Science 2024-01-11 Jiazhang Zheng , Lei Li , Qiuping Liao , Cheng Li , Li Li , Yangxing Liu