Lightweight 3-D Convolutional Occupancy Networks for Virtual Object Reconstruction-Reference-Cited by-同舟云学术

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Lightweight 3-D Convolutional Occupancy Networks for Virtual Object Reconstruction

Published:2024-03 Issue:2 Volume:44 Page:23-36
ISSN:0272-1716
Container-title:IEEE Computer Graphics and Applications
language:
Short-container-title:IEEE Comput. Grap. Appl.

Author:

Tonti Claudia Melis¹^ORCID,Papa Lorenzo¹^ORCID,Amerini Irene¹^ORCID

Affiliation:

1. Sapienza University of Rome, Rome, Italy

Funder

SERICS

MUR National Recovery and Resilience Plan

European Union - NextGenerationEU

Sapienza Università di Roma

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/38/10478455/10423209.pdf?arnumber=10423209

Reference42 articles.

1. Autonomous driving in urban environments: Boss and the Urban Challenge

2. Target-driven visual navigation in indoor scenes using deep reinforcement learning

3. A Review of Global Path Planning Methods for Occupancy Grid Maps Regardless of Obstacle Density

4. Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes

5. Adaptive local adversarial attacks on 3D point clouds

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