March 14, 2024, 4:47 a.m. | J. J. Cabrera, A. Santo, A. Gil, C. Viegas, L. Pay\'a

cs.CV updates on

arXiv:2403.07593v2 Announce Type: replace
Abstract: This paper presents MinkUNeXt, an effective and efficient architecture for place-recognition from point clouds entirely based on the new 3D MinkNeXt Block, a residual block composed of 3D sparse convolutions that follows the philosophy established by recent Transformers but purely using simple 3D convolutions. Feature extraction is performed at different scales by a U-Net encoder-decoder network and the feature aggregation of those features into a single descriptor is carried out by a Generalized Mean Pooling …

abstract architecture arxiv block cloud cloud-based feature paper philosophy recognition residual scale simple transformers type

Senior Data Engineer

@ Displate | Warsaw

Automation and AI Strategist (Remote - US)

@ MSD | USA - New Jersey - Rahway

Assistant Manager - Prognostics Development

@ Bosch Group | Bengaluru, India

Analytics Engineer - Data Solutions

@ MSD | IND - Maharashtra - Pune (Wework)

Jr. Data Engineer (temporary)

@ MSD | COL - Cundinamarca - Bogotá (Colpatria)

Senior Data Engineer

@ KION Group | Atlanta, GA, United States