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researcher

Jingwen Wang

4 papers here

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

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
ORCID 0000-0002-7413-2781
same name
  • Jingwen Wang — 11 papers, h 12
  • Jingwen Wang — 3 papers, h 5
  • Jingwen Wang — 3 papers, h 2
  • Jingwen Wang — 2 papers
  • Jingwen Wang — 2 papers, h 5
  • Jingwen Wang — 2 papers, h 2

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
20212023
most citedDSP-SLAM: Object Oriented SLAM with Deep Shape Priors

3 citations · 6 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023

SeMLaPS: Real-time Semantic Mapping with Latent Prior Networks and Quasi-Planar Segmentation

Jingwen Wang, Juan Tarrio, Lourdes Agapito +2

The availability of real-time semantics greatly improves the core geometric functionality of SLAM systems, enabling numerous robotic and AR/VR applications. We present a new method…

cs.CV2023★ 2 cited

Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM

Hengyi Wang, Jingwen Wang, Lourdes Agapito

We present Co-SLAM, a neural RGB-D SLAM system based on a hybrid representation, that performs robust camera tracking and high-fidelity surface reconstruction in real time. Co-SLAM…

cs.CV2022★ 1 cited

GO-Surf: Neural Feature Grid Optimization for Fast, High-Fidelity RGB-D Surface Reconstruction

Jingwen Wang, Tymoteusz Bleja, Lourdes Agapito

We present GO-Surf, a direct feature grid optimization method for accurate and fast surface reconstruction from RGB-D sequences. We model the underlying scene with a learned hierar…

cs.CV2021★ 3 cited

DSP-SLAM: Object Oriented SLAM with Deep Shape Priors

Jingwen Wang, Martin Rünz, Lourdes Agapito

We propose DSP-SLAM, an object-oriented SLAM system that builds a rich and accurate joint map of dense 3D models for foreground objects, and sparse landmark points to represent the…

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