PQ-Transformer: Jointly Parsing 3D Objects and Layouts From Point Clouds-Reference-Cited by-同舟云学术

PQ-Transformer: Jointly Parsing 3D Objects and Layouts From Point Clouds

Published:2022-04 Issue:2 Volume:7 Page:2519-2526
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Chen Xiaoxue¹^ORCID,Zhao Hao²^ORCID,Zhou Guyue¹^ORCID,Zhang Ya-Qin¹

Affiliation:

1. Institute for AI Industry Research, Tsinghua University, Beijing, China

2. Intel Labs China, Peking University, Beijing, China

Funder

Anker Innovations

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/9647862/09682598.pdf?arnumber=9682598

Reference37 articles.

1. ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes

2. Group-free 3D object detection via transformers;liu;Proc IEEE Int Conf Comput Vis,2021

3. Pointnet: Deep learning on point sets for 3D classification and segmentation;qi;Proc IEEE Conf Comput Vis Pattern Recognit,0

4. 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks

5. Joint 3D estimation of objects and scene layout;geiger;Adv Neural Inf Process Syst,2011

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