Results 21 to 30 of about 21,157 (187)
MDS-Net: Multi-Scale Depth Stratification 3D Object Detection from Monocular Images
Sensors, 2022 Monocular 3D object detection is very challenging in autonomous driving due to the lack of depth information. This paper proposes a one-stage monocular 3D object detection network (MDS Net), which uses the anchor-free method to detect 3D objects in a per-
Zhouzhen Xie +5 more
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Applied Sciences, 2023 Three-dimensional object detection is an essential and fundamental task in the field of computer vision which can be widely used in various scenarios such as autonomous driving and visual navigation.
Dan Zhao, Chaofeng Ji, Guizhong Liu
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eGAC3D: enhancing depth adaptive convolution and depth estimation for monocular 3D object pose detection [PDF]
PeerJ Computer Science, 2022 Many alternative approaches for 3D object detection using a singular camera have been studied instead of leveraging high-precision 3D LiDAR sensors incurring a prohibitive cost.
Duc Tuan Ngo +3 more
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OCM3D: Object-Centric Monocular 3D Object Detection
, 2021 Image-only and pseudo-LiDAR representations are commonly used for monocular 3D object detection. However, methods based on them have shortcomings of either not well capturing the spatial relationships in neighbored image pixels or being hard to handle the noisy nature of the monocular pseudo-LiDAR point cloud. To overcome these issues, in this paper we
Peng, Liang +4 more
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Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection
Proceedings of the AAAI Conference on Artificial Intelligence, 2022 Monocular 3D object detection aims to localize 3D bounding boxes in an input single 2D image. It is a highly challenging problem and remains open, especially when no extra information (e.g., depth, lidar and/or multi-frames) can be leveraged in training and/or inference.
Liu, Xianpeng, Xue, Nan, Wu, Tianfu
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Ground-Aware Monocular 3D Object Detection for Autonomous Driving [PDF]
IEEE Robotics and Automation Letters, 2021 8 pages, 6 figures, accepted by IEEE Robotics and Automation Letters (RA-L)
Yuxuan Liu, Yuan Yixuan, Ming Liu
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Homography Loss for Monocular 3D Object Detection
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 8 pages, 5 figures.
Gu, Jiaqi +6 more
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YOLOv7-3D: A Monocular 3D Traffic Object Detection Method from a Roadside Perspective
Applied Sciences, 2023 Current autonomous driving systems predominantly focus on 3D object perception from the vehicle’s perspective. However, the single-camera 3D object detection algorithm in the roadside monitoring scenario provides stereo perception of traffic objects ...
Zixun Ye +3 more
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Monocular 3D Object Detection Based on Height-Depth Constraint and Edge Fusion [PDF]
Jisuanji kexueMonocular 3D object detection aims to complete 3D object detection using monocular images,and most existing monocular 3D object detection algorithms are based on classical 2D object detection algorithms.To address the issue of inaccurate instance depth ...
PU Bin, LIANG Zhengyou, SUN Yu
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Monocular 3D Object Detection With Motion Feature Distillation
IEEE Access, 2023 In the context of autonomous driving, environmental perception within a 360-degree field of view is extremely important. This can be achieved via the detection of three-dimensional (3D) objects in the surrounding scene with the inputs acquired by sensors
Henan Hu +5 more
doaj +1 more source