research
∙
06/05/2023
Neuralangelo: High-Fidelity Neural Surface Reconstruction
Neural surface reconstruction has been shown to be powerful for recoveri...
share
research
∙
11/18/2022
Magic3D: High-Resolution Text-to-3D Content Creation
DreamFusion has recently demonstrated the utility of a pre-trained text-...
research
∙
04/13/2021
BARF: Bundle-Adjusting Neural Radiance Fields
Neural Radiance Fields (NeRF) have recently gained a surge of interest w...
research
∙
10/20/2020
SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images
Dense 3D object reconstruction from a single image has recently witnesse...
research
∙
01/27/2020
Deep NRSfM++: Towards 3D Reconstruction in the Wild
The recovery of 3D shape and pose solely from 2D landmarks stemming from...
research
∙
03/20/2019
Photometric Mesh Optimization for Video-Aligned 3D Object Reconstruction
In this paper, we address the problem of 3D object mesh reconstruction f...
research
∙
03/05/2018
ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing
We address the problem of finding realistic geometric corrections to a f...
research
∙
11/30/2017
Semantic Photometric Bundle Adjustment on Natural Sequences
The problem of obtaining dense reconstruction of an object in a natural ...
research
∙
11/04/2017
Object-Centric Photometric Bundle Adjustment with Deep Shape Prior
Reconstructing 3D shapes from a sequence of images has long been a probl...
research
∙
06/21/2017
Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction
Conventional methods of 3D object generative modeling learn volumetric p...
research
∙
05/19/2017
Deep-LK for Efficient Adaptive Object Tracking
In this paper we present a new approach for efficient regression based o...
research
∙
12/12/2016
Inverse Compositional Spatial Transformer Networks
In this paper, we establish a theoretical connection between the classic...
research
∙
03/29/2016
