Results 11 to 20 of about 3,103,629 (371)
NERF FOR HERITAGE 3D RECONSTRUCTION
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 . Conventional or learning-based 3D reconstruction methods from images have clearly shown their potential for 3D heritage documentation. Nevertheless, Neural Radiance Field (NeRF) approaches are recently revolutionising the way a scene can be rendered or
G. Mazzacca +5 more
semanticscholar +4 more sources
Occupancy Networks: Learning 3D Reconstruction in Function Space [PDF]
Computer Vision and Pattern Recognition, 2018 With the advent of deep neural networks, learning-based approaches for 3D reconstruction have gained popularity. However, unlike for images, in 3D there is no canonical representation which is both computationally and memory efficient yet allows for ...
L. Mescheder +4 more
semanticscholar +1 more source
Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery [PDF]
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2022 Reconstruction of the soft tissues in robotic surgery from endoscopic stereo videos is important for many applications such as intra-operative navigation and image-guided robotic surgery automation.
Yuehao Wang +3 more
semanticscholar +1 more source
ReconFusion: 3D Reconstruction with Diffusion Priors [PDF]
Computer Vision and Pattern Recognition, 2023 3D reconstruction methods such as Neural Radiance Fields (NeRFs) excel at rendering photorealistic novel views of complex scenes. However, recovering a high-quality NeRF typically requires tens to hundreds of input images, resulting in a time-consuming ...
Rundi Wu +10 more
semanticscholar +1 more source
Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction [PDF]
Computer Vision and Pattern Recognition, 2023 Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently struggle to capture the ...
Ziyi Yang +5 more
semanticscholar +1 more source
SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering [PDF]
Computer Vision and Pattern Recognition, 2023 We propose a method to allow precise and extremely fast mesh extraction from 3D Gaussian Splatting [15]. Gaussian Splatting has recently become very popular as it yields realistic rendering while being significantly faster to train than NeRFs.
Antoine Guédon, Vincent Lepetit
semanticscholar +1 more source
NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video [PDF]
Computer Vision and Pattern Recognition, 2021 We present a novel framework named NeuralRecon for real-time 3D scene reconstruction from a monocular video. Unlike previous methods that estimate single-view depth maps separately on each key-frame and fuse them later, we propose to directly reconstruct
Jiaming Sun +4 more
semanticscholar +1 more source
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects [PDF]
Computer Vision and Pattern Recognition, 2023 We present a near real-time (10Hz) method for 6-DoF tracking of an unknown object from a monocular RGBD video sequence, while simultaneously performing neural 3D reconstruction of the object.
Bowen Wen +8 more
semanticscholar +1 more source
3D FRONSAC with PSF reconstruction
Journal of Magnetic Resonance, 2023 10 pages, 5 ...
Yanitza Rodriguez +3 more
openaire +3 more sources
Frontiers in Surgery, 2023 ObjectiveThis study aims to explore the application value of computed tomography (CT) three-dimensional (3D) reconstruction, magnetic resonance imaging (MRI) 3D reconstruction, and conventional digital subtraction angiography (DSA) fluoroscopy in ...
Sheng-Li Zhou +5 more
doaj +1 more source