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Related papers: Shape-from-Template with Generalised Camera

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Recent years have seen the development of mature solutions for reconstructing deformable surfaces from a single image, provided that they are relatively well-textured. By contrast, recovering the 3D shape of texture-less surfaces remains an…

Computer Vision and Pattern Recognition · Computer Science 2018-07-30 Jan Bednařík , Pascal Fua , Mathieu Salzmann

We propose VideoRFSplat, a direct text-to-3D model leveraging a video generation model to generate realistic 3D Gaussian Splatting (3DGS) for unbounded real-world scenes. To generate diverse camera poses and unbounded spatial extent of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Hyojun Go , Byeongjun Park , Hyelin Nam , Byung-Hoon Kim , Hyungjin Chung , Changick Kim

We propose a general, prior-free approach for the uncalibrated non-rigid structure-from-motion problem for modelling and analysis of non-rigid objects such as human faces. The word general refers to an approach that recovers the non-rigid…

Computer Vision and Pattern Recognition · Computer Science 2018-11-26 Sami Sebastian Brandt , Hanno Ackermann , Stella Grasshof

We present To The Point (TTP), a method for reconstructing 3D objects from a single image using 2D to 3D correspondences learned from weak supervision. We recover a 3D shape from a 2D image by first regressing the 2D positions corresponding…

Computer Vision and Pattern Recognition · Computer Science 2021-06-11 Filippos Kokkinos , Iasonas Kokkinos

This paper is a theoretical study of the following Non-Rigid Structure from Motion problem. What can be computed from a monocular view of a parametrically deforming set of points? We treat various variations of this problem for affine and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Yirmeyahu Kaminski , Michael Werman

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

In this paper, we propose a learning-based framework for non-rigid shape registration without correspondence supervision. Traditional shape registration techniques typically rely on correspondences induced by extrinsic proximity, therefore…

Computer Vision and Pattern Recognition · Computer Science 2023-11-09 Puhua Jiang , Mingze Sun , Ruqi Huang

The Structure from Motion (SfM) challenge in computer vision is the process of recovering the 3D structure of a scene from a series of projective measurements that are calculated from a collection of 2D images, taken from different…

Computer Vision and Pattern Recognition · Computer Science 2023-04-06 Joseph Rowell

Estimating correspondences between deformed shape instances is a long-standing problem in computer graphics; numerous applications, from texture transfer to statistical modelling, rely on recovering an accurate correspondence map. Many…

We present a method for nonrigid registration of 2-D geometric shapes. Our contribution is twofold. First, we extend the classic chamfer-matching energy to a variational functional. Secondly, we introduce a meshless deformation model that…

Computer Vision and Pattern Recognition · Computer Science 2011-04-22 Wei Liu , Eraldo Ribeiro

In this paper, we tackle the accurate and consistent Structure from Motion (SfM) problem, in particular camera registration, far exceeding the memory of a single computer in parallel. Different from the previous methods which drastically…

Computer Vision and Pattern Recognition · Computer Science 2017-06-06 Siyu Zhu , Tianwei Shen , Lei Zhou , Runze Zhang , Jinglu Wang , Tian Fang , Long Quan

3D shape completion is important to enable machines to perceive the complete geometry of objects from partial observations. To address this problem, view-based methods have been presented. These methods represent shapes as multiple depth…

Computer Vision and Pattern Recognition · Computer Science 2019-12-02 Tao Hu , Zhizhong Han , Matthias Zwicker

Differentiable rendering is a technique to connect 3D scenes with corresponding 2D images. Since it is differentiable, processes during image formation can be learned. Previous approaches to differentiable rendering focus on mesh-based…

Computer Vision and Pattern Recognition · Computer Science 2020-03-25 Cong Gao , Xingtong Liu , Wenhao Gu , Benjamin Killeen , Mehran Armand , Russell Taylor , Mathias Unberath

Structure from Motion (SfM) refers to the problem of recovering both structure (i.e., 3D coordinates of points in the scene) and motion (i.e., camera matrices) starting from point correspondences in multiple images. It has attracted…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Federica Arrigoni

Efficient and accurate 3D object shape reconstruction contributes significantly to the success of a robot's physical interaction with its environment. Acquiring accurate shape information about unknown objects is challenging, especially in…

Robotics · Computer Science 2023-08-02 Yiting Chen , Ahmet Ercan Tekden , Marc Peter Deisenroth , Yasemin Bekiroglu

Inferring 3D structure of a generic object from a 2D image is a long-standing objective of computer vision. Conventional approaches either learn completely from CAD-generated synthetic data, which have difficulty in inference from real…

Computer Vision and Pattern Recognition · Computer Science 2021-04-05 Feng Liu , Luan Tran , Xiaoming Liu

Learning deformable 3D objects from 2D images is often an ill-posed problem. Existing methods rely on explicit supervision to establish multi-view correspondences, such as template shape models and keypoint annotations, which restricts…

Computer Vision and Pattern Recognition · Computer Science 2022-06-30 Shangzhe Wu , Tomas Jakab , Christian Rupprecht , Andrea Vedaldi

The demand for efficient 3D model generation techniques has grown exponentially, as manual creation of 3D models is time-consuming and requires specialized expertise. While generative models have shown potential in creating 3D textured…

Computer Vision and Pattern Recognition · Computer Science 2023-07-28 Fanghua Yu , Xintao Wang , Zheyuan Li , Yan-Pei Cao , Ying Shan , Chao Dong

Structure-from-Motion (SfM) aims to recover 3D scene structures and camera poses based on the correspondences between input images, and thus the ambiguity caused by duplicate structures (i.e., different structures with strong visual…

Computer Vision and Pattern Recognition · Computer Science 2022-06-14 Lei Wang , Linlin Ge , Shan Luo , Zihan Yan , Zhaopeng Cui , Jieqing Feng

Most model-free visual object tracking methods formulate the tracking task as object location estimation given by a 2D segmentation or a bounding box in each video frame. We argue that this representation is limited and instead propose to…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Denys Rozumnyi , Jiri Matas , Marc Pollefeys , Vittorio Ferrari , Martin R. Oswald