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We consider indoor 3D object detection with respect to a single RGB(-D) frame acquired from a commodity handheld device.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Sun rgb-d: A rgb-d scene understanding benchmark suite
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao · 2015
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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Ashish Vaswani · 2017
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Deep hough voting for 3d object detection in point clouds
Charles R Qi, Or Litany, Kaiming He, and Leonidas J Guibas · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Imvotenet: Boosting 3d object detection in point clouds with image votes
Charles R Qi, Xinlei Chen, Or Litany, and Leonidas J Guibas · 2020
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Accelerating 3d deep learning with pytorch3d
Nikhila Ravi, Jeremy Reizenstein, David Novotny, Taylor Gordon, Wan-Yen Lo, Justin Johnson, and Georgia Gkioxari · 2020
Cited alongside, same era.
Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
Cited alongside, same era.
Arkitscenes: A diverse real-world dataset for 3d indoor scene understanding using mobile rgb-d data
Gilad Baruch, Zhuoyuan Chen, Afshin Dehghan, Tal Dimry, Yuri Feigin, Peter Fu, Thomas Gebauer, Brandon Joffe, Daniel Kurz, Arik Schwartz, et al · 2021
Cited alongside, same era.
Multimae: Multi-modal multi-task masked autoencoders
Roman Bachmann, David Mizrahi, Andrei Atanov, and Amir Zamir · 2022
Cited alongside, same era.
Omni3d: A large benchmark and model for 3d object detection in the wild
Detr does not need multi-scale or locality design
Yutong Lin, Yuhui Yuan, Zheng Zhang, Chen Li, Nanning Zheng, and Han Hu · 2023
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Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
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Tr3d: Towards real-time indoor 3d object detection
Danila Rukhovich, Anna Vorontsova, and Anton Konushin · 2023
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Scannet++: A high-fidelity dataset of 3d indoor scenes
Chandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner, and Angela Dai · 2023
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Omninocs: A unified nocs dataset and model for 3d lifting of 2d objects
Akshay Krishnan, Abhijit Kundu, Kevis-Kokitsi Maninis, James Hays, and Matthew Brown · 2024
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Garrick Brazil, Abhinav Kumar, Julian Straub, Nikhila Ravi, Justin Johnson, and Georgia Gkioxari · 2023
Cited alongside, same era.
Perspective fields for single image camera calibration
Linyi Jin, Jianming Zhang, Yannick Hold-Geoffroy, Oliver Wang, Kevin Blackburn-Matzen, Matthew Sticha, and David F Fouhey · 2023
Cited alongside, same era.
Fcaf3d: Fully convolutional anchor-free 3d object detection
Danila Rukhovich, Anna Vorontsova, and Anton Konushin
Cited in the paper.
Imvoxelnet: Image to voxels projection for monocular and multi-view general-purpose 3d object detection
Danila Rukhovich, Anna Vorontsova, and Anton Konushin
Cited in the paper.
Depth anything: Unleashing the power of large-scale unlabeled data
Lihe Yang, Bingyi Kang, Zilong Huang, Xiaogang Xu, Jiashi Feng, and Hengshuang Zhao · 2024
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