How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Single/multi view image(s) to voxel reconstruction using a recurrent neural network
Official PyTorch implementation of the CVPR 2021 paper "Fostering Generalization in Single-view 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors". Please cite our paper and the original Occupancy Networks (Mescheder et al.) if you use this work.
Evaluation and visualization code accompanying the CVPR'19 paper "What Do Single-view 3D Reconstruction Networks Learn?" by M. Tatarchenko, S. R. Richter, R. Ranftl, Z. Li, V. Koltun, and T. Brox (*indicates equal contribution).
The main features of lmb-freiburg/what3d are: Object Reconstruction.
Projects with overlapping indexed features include: chaene/hsp — Install torch. chengjieniu/im2struct — By Chengjie Niu, Jun Li, Kai Xu. chrischoy/3d-r2n2 — Single/multi view image(s) to voxel reconstruction using a recurrent neural network. cvlab-epfl/sketch2mesh — This is the PyTorch implementation of the ICCV 2021 paper Sketch2Mesh. We provide pre-trained networks and code for… cvlab-epfl/uclid-net — This repository is the official implementation of UCLID-Net: Single View Reconstruction in Object Space (NeurIPS 2020). boschresearch/hierarchicalpriornetworks — Official PyTorch implementation of the CVPR 2021 paper "Fostering Generalization in Single-view 3D Reconstruction by…
