DeepAI AI Chat
Log In Sign Up

Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results

by   Liang Pan, et al.

As real-scanned point clouds are mostly partial due to occlusions and viewpoints, reconstructing complete 3D shapes based on incomplete observations becomes a fundamental problem for computer vision. With a single incomplete point cloud, it becomes the partial point cloud completion problem. Given multiple different observations, 3D reconstruction can be addressed by performing partial-to-partial point cloud registration. Recently, a large-scale Multi-View Partial (MVP) point cloud dataset has been released, which consists of over 100,000 high-quality virtual-scanned partial point clouds. Based on the MVP dataset, this paper reports methods and results in the Multi-View Partial Point Cloud Challenge 2021 on Completion and Registration. In total, 128 participants registered for the competition, and 31 teams made valid submissions. The top-ranked solutions will be analyzed, and then we will discuss future research directions.


page 4

page 5


Weakly-supervised 3D Shape Completion in the Wild

3D shape completion for real data is important but challenging, since pa...

HyperPocket: Generative Point Cloud Completion

Scanning real-life scenes with modern registration devices typically giv...

Consistent Two-Flow Network for Tele-Registration of Point Clouds

Rigid registration of partial observations is a fundamental problem in v...

Deep Models with Fusion Strategies for MVP Point Cloud Registration

The main goal of point cloud registration in Multi-View Partial (MVP) Ch...

Multi-view Point Cloud Registration with Adaptive Convergence Threshold and its Application on 3D Model Retrieval

Multi-view point cloud registration is a hot topic in the communities of...

Multi-view Point Cloud Registration based on Evolutionary Multitasking with Bi-Channel Knowledge Sharing Mechanism

Registration of multi-view point clouds is fundamental in 3D reconstruct...

Spotlights: Probing Shapes from Spherical Viewpoints

Recent years have witnessed the surge of learned representations that di...