Learning to Generate Realistic LiDAR Point Clouds

Learning to Generate Realistic LiDAR Point Clouds

8 September 2022

Shenlong Wang

Papers citing "Learning to Generate Realistic LiDAR Point Clouds"

9 / 9 papers shown

Title
DRAWER: Digital Reconstruction and Articulation With Environment Realism Hongchi Xia Entong Su Marius Memmel Arhan Jain Raymond Yu Numfor Mbiziwo-Tiapo Ali Farhadi Abhishek Gupta Shenlong Wang Wei-Chiu Ma VGen 14 0 0 21 Apr 2025
RS2AD: End-to-End Autonomous Driving Data Generation from Roadside Sensor Observations Ruidan Xing Runyi Huang Qing Xu Lei He 47 0 0 10 Mar 2025
Transfer Your Perspective: Controllable 3D Generation from Any Viewpoint in a Driving Scene Tai-Yu Pan Sooyoung Jeon Mengdi Fan Jinsu Yoo Zhenyang Feng Mark E. Campbell Kilian Q. Weinberger Bharath Hariharan Wei-Lun Chao 88 0 0 10 Feb 2025
MObI: Multimodal Object Inpainting Using Diffusion Models Alexandru Buburuzan Anuj Sharma John Redford P. Dokania Romain Mueller DiffM 54 1 0 06 Jan 2025
Diffusion Probabilistic Models for 3D Point Cloud Generation Shitong Luo Wei Hu 3DPC 158 566 0 02 Mar 2021
Deep Generative Modeling of LiDAR Data Lucas Page-Caccia H. V. Hoof Aaron Courville Joelle Pineau 3DPC 127 55 0 04 Dec 2018
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters Yifan Xu Tianqi Fan Mingye Xu Long Zeng Yu Qiao 3DV 3DPC 137 707 0 30 Mar 2018
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 199 12,351 0 02 Dec 2016
Image-to-Image Translation with Conditional Adversarial Networks Phillip Isola Jun-Yan Zhu Tinghui Zhou Alexei A. Efros SSeg 203 7,006 0 21 Nov 2016