Projects sharing features with Multimodal Shape Completion

MonoScene: Monocular 3D Semantic Scene Completion\ Anh-Quan Cao, Raoul de Charette Inria, Paris, France. CVPR 2022 \

Note: An updated and improved version of this approach is available as pre-print on ArXiv and the corresponding repository is davidstutz/arxiv2018-improved-shape-completion.

Code for ECCV 2022 paper PatchRD: Detail-Preserving Shape Completion by Learning Patch Retrieval and Deformation

Official Repository of CVPR 2019 Paper : RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion

Pytorch code for the paper "Data-driven Restoration of Cultural Heritage Objects with Point Cloud Analysis" by Ivan Sipiran, Alexis Mendoza, Alexander Apaza and Cristian Lopez.

This repository is for SSA-SC introduced in the following paper. [arxiv paper](https://arxiv.org/pdf/2109.11453.pdf)

ArXiv | BibTex We develop a new approach for image inpainting that does a better job of reproducing filled regions exhibiting fine details inspired by our understanding of how artists work: lines first, color next. We propose a two-stage adversarial model EdgeConnect that comprises of an edge…

This repository contains a Tensorflow implementation of the paper:

This repository contains source code for all methods used for the Stanford 3D Object Point Cloud Completion Benchmark and presented in the paper TopNet: Structural Point Cloud Decoder, CVPR 2019.

New Repo

IIAU (2019) 3D Semantic Scene Completion Introduction This file contains our Semantic Scene Completion models appeared in ICCV2019. 1) CCPNet Title: Cascaded Context Pyramid for Full-Resolution 3D Semantic Scene Completion Authors: Pingping Zhang, Wei Liu, Yinjie Lei, Huchuan Luand Xiaoyun Yang…

DeformingThings4D is an synthetic dataset containing 1,972 animation sequences spanning 31 categories of humanoids and animals.

This repo contains training and testing code for our paper on semantic scene completion, a task for producing a complete 3D voxel representation of volumetric occupancy and semantic labels for a scene from a single-view depth map observation. More information about the project can be found in…

Supplementary Code for the CVPR'19 paper entitled Leveraging Shape Completion for 3D Siamese Tracking

This is the anonymous demo code for the ICCV submission.

The implementation of our paper accepted in ICCV 2019 (International Conference on Computer Vision, IEEE)

AICNet (CVPR2020): Anisotropic Convolutional Networks for 3D Semantic Scene Completion - DDRNet (CVPR2019): RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion - PALNet (RAL2019): Depth Based Semantic Scene Completion with Position Importance Aware Loss

PCN is a learning-based shape completion method which directly maps a partial point cloud to a dense, complete point cloud without any voxelization. It is based on our 3DV 2018 publication PCN: Point Completion Network. Please refer to our project website or read our paper for more details.

This is the new repository from the original one (https://github.com/xiaogangw-zz/cascaded-point-completion), all the contents are the same.

This is the PyTorch implementation for the paper "Voxel-based Network for Shape Completion by Leveraging Edge Generation (ICCV 2021, oral)"

Implementation of ICLR 2020 paper (link) .

Semantic Scene Completion via Integrating Instances and Scene in-the-Loop (CVPR 2021)

ICCV 2021 Oral PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

Created by Jiahui Zhang, Hao Zhao, Anbang Yao, Yurong Chen, Li Zhang and Hongen Liao