English
Related papers

Related papers: Structure from Collision

200 papers

We present Neural Articulated Radiance Field (NARF), a novel deformable 3D representation for articulated objects learned from images. While recent advances in 3D implicit representation have made it possible to learn models of complex…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Atsuhiro Noguchi , Xiao Sun , Stephen Lin , Tatsuya Harada

We present ObSuRF, a method which turns a single image of a scene into a 3D model represented as a set of Neural Radiance Fields (NeRFs), with each NeRF corresponding to a different object. A single forward pass of an encoder network…

Computer Vision and Pattern Recognition · Computer Science 2021-04-05 Karl Stelzner , Kristian Kersting , Adam R. Kosiorek

We present a method for estimating neural scenes representations of objects given only a single image. The core of our method is the estimation of a geometric scaffold for the object and its use as a guide for the reconstruction of the…

Computer Vision and Pattern Recognition · Computer Science 2021-06-24 Konstantinos Rematas , Ricardo Martin-Brualla , Vittorio Ferrari

Non-Rigid Structure from Motion (NRSfM) refers to the problem of reconstructing cameras and the 3D point cloud of a non-rigid object from an ensemble of images with 2D correspondences. Current NRSfM algorithms are limited from two…

Computer Vision and Pattern Recognition · Computer Science 2019-09-10 Chen Kong , Simon Lucey

In advanced mission concepts with high levels of autonomy, spacecraft need to internally model the pose and shape of nearby orbiting objects. Recent works in neural scene representations show promising results for inferring generic…

Computer Vision and Pattern Recognition · Computer Science 2021-05-14 Anne Mergy , Gurvan Lecuyer , Dawa Derksen , Dario Izzo

In the realm of digital situational awareness during disaster situations, accurate digital representations, like 3D models, play an indispensable role. To ensure the safety of rescue teams, robotic platforms are often deployed to generate…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Hartmut Surmann , Niklas Digakis , Jan-Nicklas Kremer , Julien Meine , Max Schulte , Niklas Voigt

Realistic face rendering from multi-view images is beneficial to various computer vision and graphics applications. Due to the complex spatially-varying reflectance properties and geometry characteristics of faces, however, it remains…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Mingwu Zheng , Haiyu Zhang , Hongyu Yang , Di Huang

Neural implicit 3D representations have emerged as a powerful paradigm for reconstructing surfaces from multi-view images and synthesizing novel views. Unfortunately, existing methods such as DVR or IDR require accurate per-pixel object…

Computer Vision and Pattern Recognition · Computer Science 2021-10-11 Michael Oechsle , Songyou Peng , Andreas Geiger

Vision-based 3D semantic scene completion (SSC) describes autonomous driving scenes through 3D volume representations. However, the occlusion of invisible voxels by scene surfaces poses challenges to current SSC methods in hallucinating…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Xiao Zhao , Bo Chen , Mingyang Sun , Dingkang Yang , Youxing Wang , Xukun Zhang , Mingcheng Li , Dongliang Kou , Xiaoyi Wei , Lihua Zhang

This paper presents Neural Mesh Fusion (NMF), an efficient approach for joint optimization of polygon mesh from multi-view image observations and unsupervised 3D planar-surface parsing of the scene. In contrast to implicit neural…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Farhad G. Zanjani , Hong Cai , Yinhao Zhu , Leyla Mirvakhabova , Fatih Porikli

In this work, we present a new method for 3D face reconstruction from sparse-view RGB images. Unlike previous methods which are built upon 3D morphable models (3DMMs) with limited details, we leverage an implicit representation to encode…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Moran Li , Haibin Huang , Yi Zheng , Mengtian Li , Nong Sang , Chongyang Ma

A practical benefit of implicit visual representations like Neural Radiance Fields (NeRFs) is their memory efficiency: large scenes can be efficiently stored and shared as small neural nets instead of collections of images. However,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Jiading Fang , Shengjie Lin , Igor Vasiljevic , Vitor Guizilini , Rares Ambrus , Adrien Gaidon , Gregory Shakhnarovich , Matthew R. Walter

We present a novel method, called NeuralUDF, for reconstructing surfaces with arbitrary topologies from 2D images via volume rendering. Recent advances in neural rendering based reconstruction have achieved compelling results. However,…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Xiaoxiao Long , Cheng Lin , Lingjie Liu , Yuan Liu , Peng Wang , Christian Theobalt , Taku Komura , Wenping Wang

Neural Radiance Fields (NeRF) have constituted a remarkable breakthrough in image-based 3D reconstruction. However, their implicit volumetric representations differ significantly from the widely-adopted polygonal meshes and lack support…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Jiaxiang Tang , Hang Zhou , Xiaokang Chen , Tianshu Hu , Errui Ding , Jingdong Wang , Gang Zeng

Obtaining a better knowledge of the current state and behavior of objects orbiting Earth has proven to be essential for a range of applications such as active debris removal, in-orbit maintenance, or anomaly detection. 3D models represent a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Clément Forray , Pauline Delporte , Nicolas Delaygue , Florence Genin , Dawa Derksen

Neural Radiance Fields (NeRFs) have emerged as a groundbreaking paradigm for representing 3D objects and scenes by encoding shape and appearance information into the weights of a neural network. Recent studies have demonstrated that these…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Francesco Ballerini , Pierluigi Zama Ramirez , Luigi Di Stefano , Samuele Salti

Neural scene representations such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have transformed how 3D environments are modeled, rendered, and interpreted. NeRF introduced view-consistent photorealism via volumetric…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Javed Ahmad , Penggang Gao , Donatien Delehelle , Mennuti Canio , Nikhil Deshpande , Jesús Ortiz , Darwin G. Caldwell , Yonas Teodros Tefera

A variety of Neural Radiance Fields (NeRF) methods have recently achieved remarkable success in high render speed. However, current accelerating methods are specialized and incompatible with various implicit methods, preventing real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Xinyu Gao , Ziyi Yang , Yunlu Zhao , Yuxiang Sun , Xiaogang Jin , Changqing Zou

Visualizing surgical scenes is crucial for revealing internal anatomical structures during minimally invasive procedures. Novel View Synthesis is a vital technique that offers geometry and appearance reconstruction, enhancing understanding,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Jiaxin Guo , Jiangliu Wang , Ruofeng Wei , Di Kang , Qi Dou , Yun-hui Liu

Contemporary registration devices for 3D visual information, such as LIDARs and various depth cameras, capture data as 3D point clouds. In turn, such clouds are challenging to be processed due to their size and complexity. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Dominik Zimny , Joanna Waczyńska , Tomasz Trzciński , Przemysław Spurek