Monocular 3D Object Detection With Motion Feature Distillation

Hu, Henan; Li, Muyu; Zhu, Ming; Gao, Wen; Liu, Peiyu; Chan, Kwok-Leung

doi:10.1109/access.2023.3300708

IEEE Access

2023

DOI: 10.1109/access.2023.3300708

|View full text |Cite

Monocular 3D Object Detection With Motion Feature Distillation

Henan Hu,

Muyu Li,

Ming Zhu

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

VKP-P3D: Real-Time Monocular Pseudo 3D Object Detection Based on Visible Key Points and Camera Geometry

Sun,

Liu,

Xiao

et al. 2024

IEEE Access

View full text Add to dashboard Cite

Three-dimensional object detection has been substantially improved with the use of expensive LiDAR and stereo vision systems in intelligent driving. The less-expensive and more scalable solution of monocular 3D object detection, however, remains a key challenge. This study primarily explores real-time pseudo 3D object detection with monocular vision and designs a single-shot RPN model, VKP-P3D, which relies purely on visual feature extraction. Through a multiscale feature fusion and an attention mechanism module, this model obtains high-dimensional feature representations during the feature extraction phase. In the detection head of the VKP-P3D model, the pseudo 3D object detection is obtained by regressing 2D bounding box and the visible key points within the image coordinate of the 3D box from the camera's perspective. Finally, assuming flat ground and considering geometric parameters of the camera, the object's 3D information can be extracted. To verify the effectiveness of the proposed algorithm, we constructed two pseudo 3D object detection datasets based on visible key points and compared with current state-of-the-art real-time object detector. Results showed that the proposed model has high detection accuracy and speed.INDEX TERMS Monocular vision, pseudo 3D object detection, visual key point, single-shot RPN network.

show abstract

VKP-P3D: Real-Time Monocular Pseudo 3D Object Detection Based on Visible Key Points and Camera Geometry

Sun,

Liu,

Xiao

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

Semantic Shape and Trajectory Reconstruction for Monocular Cooperative 3D Object Detection

Cserni,

Rövid

2024

IEEE Access

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Monocular 3D Object Detection With Motion Feature Distillation

Cited by 2 publications

References 16 publications

VKP-P3D: Real-Time Monocular Pseudo 3D Object Detection Based on Visible Key Points and Camera Geometry

VKP-P3D: Real-Time Monocular Pseudo 3D Object Detection Based on Visible Key Points and Camera Geometry

Semantic Shape and Trajectory Reconstruction for Monocular Cooperative 3D Object Detection

Contact Info

Product

Resources

About