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M. Matteucci

28 papers hereh-index 427.3k citations302 works total

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

author position
  • middle author8
  • last author20

Across the 28 of 28 papers where every author was matched, so the position is known.

fields
  • cs.CV18
  • cs.RO5
  • cs.LG2
  • cs.IT1
  • eess.SP1
  • eess.SY1
same name
  • M. Matteucci — 1 paper, h 16
  • M. Matteucci — 1 paper, h 3

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
20162021
most citedMesh-based Camera Pairs Selection and Occlusion-Aware Masking for Mesh Refinement

13 citations · 22 across the 9 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.RO2019★ 2 cited

Towards Affordance Prediction with Vision via Task Oriented Grasp Quality Metrics

Luca Cavalli, Gianpaolo Di Pietro, Matteo Matteucci

While many quality metrics exist to evaluate the quality of a grasp by itself, no clear quantification of the quality of a grasp relatively to the task the grasp is used for has be…

cs.CV2019★ 13 cited

Mesh-based Camera Pairs Selection and Occlusion-Aware Masking for Mesh Refinement

Andrea Romanoni, Matteo Matteucci

Many Multi-View-Stereo algorithms extract a 3D mesh model of a scene, after fusing depth maps into a volumetric representation of the space. Due to the limited scalability of such…

cs.CV2019

TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo

Andrea Romanoni, Matteo Matteucci

One of the most successful approaches in Multi-View Stereo estimates a depth map and a normal map for each view via PatchMatch-based optimization and fuses them into a consistent 3…

cs.CV2019

Dense 3D Visual Mapping via Semantic Simplification

Luca Morreale, Andrea Romanoni, Matteo Matteucci

Dense 3D visual mapping estimates as many as possible pixel depths, for each image. This results in very dense point clouds that often contain redundant and noisy information, espe…

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