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Stefano Rosa

12 papers hereh-index 163.4k citations58 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author11
  • last author1

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV8
  • cs.RO2
  • cs.NE1
  • eess.SP1
same name
  • Stefano Rosa — 5 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162023
most citedLearning Semantic Segmentation of Large-Scale Point Clouds with Random Sampling

224 citations · 230 across the 4 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019

RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

Qingyong Hu, Bo Yang, Linhai Xie +5

We study the problem of efficient semantic segmentation for large-scale 3D point clouds. By relying on expensive sampling techniques or computationally heavy pre/post-processing st…

eess.SP2019

See Through Smoke: Robust Indoor Mapping with Low-cost mmWave Radar

Chris Xiaoxuan Lu, Stefano Rosa, Peijun Zhao +5

This paper presents the design, implementation and evaluation of milliMap, a single-chip millimetre wave (mmWave) radar based indoor mapping system targetted towards low-visibility…

cs.CV2019

DeepTIO: A Deep Thermal-Inertial Odometry with Visual Hallucination

Muhamad Risqi U. Saputra, Pedro P. B. de Gusmao, Chris Xiaoxuan Lu +7

Visual odometry shows excellent performance in a wide range of environments. However, in visually-denied scenarios (e.g. heavy smoke or darkness), pose estimates degrade or even fa…

cs.CV2019★ 6 cited

Selective Sensor Fusion for Neural Visual-Inertial Odometry

Changhao Chen, Stefano Rosa, Yishu Miao +4

Deep learning approaches for Visual-Inertial Odometry (VIO) have proven successful, but they rarely focus on incorporating robust fusion strategies for dealing with imperfect input…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.