RecNet: An Invertible Point Cloud Encoding through Range Image
Embeddings for Multi-Robot Map Sharing and Reconstruction

RecNet: An Invertible Point Cloud Encoding through Range Image Embeddings for Multi-Robot Map Sharing and Reconstruction

3 February 2024

Nikolaos Stathoulopoulos

Mario A. V. Saucedo

G. Nikolakopoulos

Papers citing "RecNet: An Invertible Point Cloud Encoding through Range Image Embeddings for Multi-Robot Map Sharing and Reconstruction"

4 / 4 papers shown

Title
Why Sample Space Matters: Keyframe Sampling Optimization for LiDAR-based Place Recognition Nikolaos Stathoulopoulos Vidya Sumathy Christoforos Kanellakis G. Nikolakopoulos 76 1 0 20 Feb 2025
LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition Kavisha Vidanapathirana Milad Ramezani Peyman Moghadam S. Sridharan Clinton Fookes 3DPC 3DV 31 81 0 17 Sep 2021
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 219 13,886 0 02 Dec 2016
SegMatch: Segment based loop-closure for 3D point clouds Renaud Dubé Daniel Dugas E. Stumm Juan I. Nieto Roland Siegwart César Cadena 3DV 190 316 0 25 Sep 2016