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This paper addresses the problem of estimating the 3-DoF camera pose for a ground-level image with respect to a satellite image that encompasses the local surroundings. We propose a novel end-to-end approach that leverages the learning of…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Zhenbo Song , Xianghui Ze , Jianfeng Lu , Yujiao Shi

We present a stereo-based dense mapping algorithm for large-scale dynamic urban environments. In contrast to other existing methods, we simultaneously reconstruct the static background, the moving objects, and the potentially moving but…

Computer Vision and Pattern Recognition · Computer Science 2019-05-09 Ioan Andrei Bârsan , Peidong Liu , Marc Pollefeys , Andreas Geiger

Establishing dense correspondences between a pair of images is an important and general problem. However, dense flow estimation is often inaccurate in the case of large displacements or homogeneous regions. For most applications and…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Prune Truong , Martin Danelljan , Luc Van Gool , Radu Timofte

We describe a method to extract persistent elements of a dynamic scene from an input video. We represent each scene element as a \emph{Deformable Sprite} consisting of three components: 1) a 2D texture image for the entire video, 2)…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Vickie Ye , Zhengqi Li , Richard Tucker , Angjoo Kanazawa , Noah Snavely

In recent years, consumer-level depth cameras have been adopted for various applications. However, they often produce depth maps at only a moderately high frame rate (approximately 30 frames per second), preventing them from being used for…

Graphics · Computer Science 2018-11-06 Ming-Ze Yuan , Lin Gao , Hongbo Fu , Shihong Xia

Video generative models have made remarkable progress, yet they often yield visual artifacts that violate grounding in physical dynamics. Recent works such as PhysGen3D tackle single image-to-3D physics through mesh reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Hwidong Kim , Yunho Kim , Tae-Kyun Kim

Our goal in this work is to generate realistic videos given just one initial frame as input. Existing unsupervised approaches to this task do not consider the fact that a video typically shows a 3D environment, and that this should remain…

Computer Vision and Pattern Recognition · Computer Science 2021-06-18 Paul Henderson , Christoph H. Lampert , Bernd Bickel

In this paper, we present RStab, a novel framework for video stabilization that integrates 3D multi-frame fusion through volume rendering. Departing from conventional methods, we introduce a 3D multi-frame perspective to generate stabilized…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Zhan Peng , Xinyi Ye , Weiyue Zhao , Tianqi Liu , Huiqiang Sun , Baopu Li , Zhiguo Cao

This paper presents DENSER, an efficient and effective approach leveraging 3D Gaussian splatting (3DGS) for the reconstruction of dynamic urban environments. While several methods for photorealistic scene representations, both implicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Mahmud A. Mohamad , Gamal Elghazaly , Arthur Hubert , Raphael Frank

Event-based cameras can overpass frame-based cameras limitations for important tasks such as high-speed motion detection during self-driving cars navigation in low illumination conditions. The event cameras' high temporal resolution and…

Computer Vision and Pattern Recognition · Computer Science 2022-01-31 Haixin Sun , Minh-Quan Dao , Vincent Fremont

The increasing number of cameras and a handful of human operators to monitor the video inputs from hundreds of cameras leave the system ill equipped to fulfil the task of detecting anomalies. Thus, there is a dire need to automatically…

Computer Vision and Pattern Recognition · Computer Science 2014-10-16 Mei Kuan Lim , Chee Seng Chan , Dorothy Monekosso , Paolo Remagnino

In this paper, we present a new model to simulate the formation, evolution, and break up of a thin film of fluid flowing over a curved surface. Referred to as the discrete droplet method (DDM), the model captures the evolution of thin fluid…

Fluid Dynamics · Physics 2022-10-20 Anand S Bharadwaj , Joerg Kuhnert , Stephane P. A. Bordas , Pratik Suchde

Generative models that can model and predict sequences of future events can, in principle, learn to capture complex real-world phenomena, such as physical interactions. However, a central challenge in video prediction is that the future is…

Computer Vision and Pattern Recognition · Computer Science 2020-02-13 Manoj Kumar , Mohammad Babaeizadeh , Dumitru Erhan , Chelsea Finn , Sergey Levine , Laurent Dinh , Durk Kingma

Reconstructing clean, distractor-free 3D scenes from real-world captures remains a significant challenge, particularly in highly dynamic and cluttered settings such as egocentric videos. To tackle this problem, we introduce DeGauss, a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Rui Wang , Quentin Lohmeyer , Mirko Meboldt , Siyu Tang

We introduce a method and a 3D-camera for single-shot 3D shape measurement, with unprecedented features: The 3D-camera does not rely on pattern codification and acquires object surfaces at the theoretical limit of the information…

Optics · Physics 2017-10-11 Florian Willomitzer , Gerd Häusler

Performing facial expression transfer under one-shot setting has been increasing in popularity among research community with a focus on precise control of expressions. Existing techniques showcase compelling results in perceiving…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Siddharth Nijhawan , Takuya Yashima , Tamaki Kojima

Hyperspectral 3D imaging captures both depth maps and hyperspectral images, enabling comprehensive geometric and material analysis. Recent methods achieve high spectral and depth accuracy; however, they require long acquisition times often…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Suhyun Shin , Seungwoo Yoon , Ryota Maeda , Seung-Hwan Baek

Reconstructing 3D geometry and appearance from a sparse set of fixed cameras is a foundational task with broad applications, yet it remains fundamentally constrained by the limited viewpoints. We show that this bound can be broken by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Ryosuke Hirai , Kohei Yamashita , Antoine Guédon , Ryo Kawahara , Vincent Lepetit , Ko Nishino

Thin structures, such as wire-frame sculptures, fences, cables, power lines, and tree branches, are common in the real world. It is extremely challenging to acquire their 3D digital models using traditional image-based or depth-based…

Graphics · Computer Science 2020-05-21 Peng Wang , Lingjie Liu , Nenglun Chen , Hung-Kuo Chu , Christian Theobalt , Wenping Wang

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