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ZoomNet: Part-Aware Adaptive Zooming Neural Network for 3D Object Detection
[article]
2020
arXiv
pre-print
Preserved Fulltext
In this paper, we present a novel framework named ZoomNet for stereo imagery-based 3D detection. ...
3D object detection is an essential task in autonomous driving and robotics. Though great progress has been made, challenges remain in estimating 3D pose for distant and occluded objects. ...
In this paper, we propose adaptive zooming as an effective strategy to obtain better 3D detection results for distant cars. Part-aware neural networks. ...
arXiv:2003.00529v1
fatcat:kfcz5eoqvnaflhhlfqt6mkeb7a
ZoomNet: Part-Aware Adaptive Zooming Neural Network for 3D Object Detection
2020
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this paper, we present a novel framework named ZoomNet for stereo imagery-based 3D detection. ...
3D object detection is an essential task in autonomous driving and robotics. Though great progress has been made, challenges remain in estimating 3D pose for distant and occluded objects. ...
In this paper, we propose adaptive zooming as an effective strategy to obtain better 3D detection results for distant cars. Part-aware neural networks. ...
doi:10.1609/aaai.v34i07.6945
fatcat:wngiiy3npvdxpnxvz5vzjassnm
LIGA-Stereo: Learning LiDAR Geometry Aware Representations for Stereo-based 3D Detector
[article]
2021
arXiv
pre-print
Preserved Fulltext
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The file type is application/pdf.
Stereo-based 3D detection aims at detecting 3D object bounding boxes from stereo images using intermediate depth maps or implicit 3D geometry representations, which provides a low-cost solution for 3D ...
To solve the problem, we propose LIGA-Stereo (LiDAR Geometry Aware Stereo Detector) to learn stereo-based 3D detectors under the guidance of high-level geometry-aware representations of LiDAR-based detection ...
Zoomnet: Part-aware adaptive zooming neural network for [71] Yin Zhou and Oncel Tuzel. Voxelnet: End-to-end learning
3d object detection. ...
arXiv:2108.08258v1
fatcat:hz7ix7azmfbf3oli7mpay7jf3a
Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection
[article]
2021
arXiv
pre-print
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The file type is application/pdf.
Monocular 3D object detection aims to localize 3D bounding boxes in an input single 2D image. ...
This paper proposes a simple yet effective formulation for monocular 3D object detection without exploiting any extra information. ...
Zoomnet: Part-aware
A metric and a loss for bounding box regression. In CVPR, adaptive zooming neural network for 3d object detection. ...
arXiv:2112.04628v1
fatcat:e5ev2xesvjgmpe5cfm57cscu6i
Recent Advances of Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective
2022
ACM Computing Surveys
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The file type is application/pdf.
Especially, we provide insightful analyses for the intrinsic connections and methods evolution from 2D to 3D pose estimation. ...
Furthermore, we analyze the solutions for challenging cases, such as the lack of data, the inherent ambiguity between 2D and 3D, and the complex multi-person scenarios. ...
Microsoft Common Objects in COntext (MSCOCO) Dataset [112] contains annotations for object detection, panoptic segmentation, and keypoint detection. ...
doi:10.1145/3524497
fatcat:4pbvntngrnfp7lqhcpjmy7p2fq
Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective
[article]
2021
arXiv
pre-print
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2D and 3D, and the complex multi-person scenarios. ...
Finally, we discuss the challenges and give deep thinking of promising directions for future research. ...
: 0.95), AP M for medium objects, AP L for large objects, AR 0.5 , AR 0.75 , AR, AR M for medium objects, AR L for large objects. ...
arXiv:2104.11536v1
fatcat:tdag2jq2vjdrjekwukm5nu7l6a
Pseudo-LiDAR: Camera-based 3D object detection for autonomous driving
2021
Preserved Fulltext
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2021 3D object detection is an essential task in autonomous driving. ...
Finally, we unify the depth estimation and 3D object detection tasks and perform them in the same metric space. ...
Nevertheless, future work on 3D object detection using stereo must be aware of this overlap. Monocular depth estimation. ...
doi:10.7298/dk5h-ps13
fatcat:vpk4iw3lknejhp64qjj6lr67ru