Recursive Rendering of 2D Images for Accurate Pose Estimation in a 3D Mesh Map-Reference-Cited by-同舟云学术

Recursive Rendering of 2D Images for Accurate Pose Estimation in a 3D Mesh Map

Published:2022-12-06 Issue: Volume: Page:
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Container-title:SIGGRAPH Asia 2022 Posters
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Author:

Hanaoka Yohei¹^ORCID,Suwanwimolkul Suwichaya¹^ORCID,Komorita Satoshi¹^ORCID

Affiliation:

1. KDDI Research, Inc., Japan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3550082.3564201

Reference6 articles.

1. Yohei Hanaoka Suwichaya Suwanwimolkul and Satoshi Komorita. 2022. tokyo-localization-2022 dataset. https://github.com/yohanaoka/tokyo-localization-2022. Yohei Hanaoka Suwichaya Suwanwimolkul and Satoshi Komorita. 2022. tokyo-localization-2022 dataset. https://github.com/yohanaoka/tokyo-localization-2022.

2. Analysis of Compass Sensor Accuracy on Several Mobile Devices in an Industrial Environment

3. Ministry of Land Infrastructure Transport and Tourism. 2020. PLATEAU. https://www.mlit.go.jp/plateau/. Ministry of Land Infrastructure Transport and Tourism. 2020. PLATEAU. https://www.mlit.go.jp/plateau/.

4. Jerome Revaud Philippe Weinzaepfel César Roberto de Souza and Martin Humenberger. 2019. R2D2: Repeatable and Reliable Detector and Descriptor. In NeurIPS. Jerome Revaud Philippe Weinzaepfel César Roberto de Souza and Martin Humenberger. 2019. R2D2: Repeatable and Reliable Detector and Descriptor. In NeurIPS.

5. LoFTR: Detector-Free Local Feature Matching with Transformers

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