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Matheus Gadelha

17 papers hereh-index 121.3k citations23 works total

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

author position
  • first author7
  • middle author9
  • last author1

Across the 17 of 17 papers where every author was matched, so the position is known.

fields
  • cs.CV17
same name
  • Matheus Gadelha — 8 papers, h 6
  • Matheus Gadelha — 7 papers, h 3
  • Matheus Gadelha — 5 papers, h 2
  • Matheus Gadelha — 4 papers, h 5

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
20162026
most citedMultiresolution Tree Networks for 3D Point Cloud Processing

41 citations · 115 across the 15 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022

Accidental Turntables: Learning 3D Pose by Watching Objects Turn

Zezhou Cheng, Matheus Gadelha, Subhransu Maji

We propose a technique for learning single-view 3D object pose estimation models by utilizing a new source of data -- in-the-wild videos where objects turn. Such videos are prevale…

cs.CV2022

Recovering Detail in 3D Shapes Using Disparity Maps

Marissa Ramirez de Chanlatte, Matheus Gadelha, Thibault Groueix +1

We present a fine-tuning method to improve the appearance of 3D geometries reconstructed from single images. We leverage advances in monocular depth estimation to obtain disparity…

cs.CV2022★ 1 cited

PlanarRecon: Real-time 3D Plane Detection and Reconstruction from Posed Monocular Videos

Yiming Xie, Matheus Gadelha, Fengting Yang +2

We present PlanarRecon -- a novel framework for globally coherent detection and reconstruction of 3D planes from a posed monocular video. Unlike previous works that detect planes i…

cs.CV2022★ 7 cited

ANISE: Assembly-based Neural Implicit Surface rEconstruction

Dmitry Petrov, Matheus Gadelha, Radomir Mech +1

We present ANISE, a method that reconstructs a 3D~shape from partial observations (images or sparse point clouds) using a part-aware neural implicit shape representation. The shape…

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