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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Geometry-Constrained Car Recognition Using a 3D Perspective Network

February 1, 2023

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Authors

Zeng Rui

Queensland University of Technology


Ge Zongyuan

Monash University


Denman Simon

Queensland University of Technology


Sridharan Sridha

Queensland University of Technology


Fookes Clinton

Queensland University of Technology


DOI:

10.1609/aaai.v34i01.5468


Abstract:

We present a novel learning framework for vehicle recognition from a single RGB image. Unlike existing methods which only use attention mechanisms to locate 2D discriminative information, our work learns a novel 3D perspective feature representation of a vehicle, which is then fused with 2D appearance feature to predict the category. The framework is composed of a global network (GN), a 3D perspective network (3DPN), and a fusion network. The GN is used to locate the region of interest (RoI) and generate the 2D global feature. With the assistance of the RoI, the 3DPN estimates the 3D bounding box under the guidance of the proposed vanishing point loss, which provides a perspective geometry constraint. Then the proposed 3D representation is generated by eliminating the viewpoint variance of the 3D bounding box using perspective transformation. Finally, the 3D and 2D feature are fused to predict the category of the vehicle. We present qualitative and quantitative results on the vehicle classification and verification tasks in the BoxCars dataset. The results demonstrate that, by learning such a concise 3D representation, we can achieve superior performance to methods that only use 2D information while retain 3D meaningful information without the challenge of requiring a 3D CAD model.

Topics: AAAI

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HOW TO CITE:

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton Geometry-Constrained Car Recognition Using a 3D Perspective Network Proceedings of the AAAI Conference on Artificial Intelligence (2020) 1161-1168.

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton Geometry-Constrained Car Recognition Using a 3D Perspective Network AAAI 2020, 1161-1168.

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton (2020). Geometry-Constrained Car Recognition Using a 3D Perspective Network. Proceedings of the AAAI Conference on Artificial Intelligence, 1161-1168.

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton. Geometry-Constrained Car Recognition Using a 3D Perspective Network. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.1161-1168.

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton. 2020. Geometry-Constrained Car Recognition Using a 3D Perspective Network. "Proceedings of the AAAI Conference on Artificial Intelligence". 1161-1168.

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton. (2020) "Geometry-Constrained Car Recognition Using a 3D Perspective Network", Proceedings of the AAAI Conference on Artificial Intelligence, p.1161-1168

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton, "Geometry-Constrained Car Recognition Using a 3D Perspective Network", AAAI, p.1161-1168, 2020.

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton. "Geometry-Constrained Car Recognition Using a 3D Perspective Network". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.1161-1168.

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton. "Geometry-Constrained Car Recognition Using a 3D Perspective Network". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 1161-1168.

Zeng Rui||Ge Zongyuan||Denman Simon||Sridharan Sridha||Fookes Clinton. Geometry-Constrained Car Recognition Using a 3D Perspective Network. AAAI[Internet]. 2020[cited 2023]; 1161-1168.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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