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Lite-FPN for Keypoint-based Monocular 3D Object Detection
[article]
2021
arXiv
pre-print
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Recently, keypoint-based monocular 3D object detection has made tremendous progress and achieved great speed-accuracy trade-off. ...
3D object detection with a single image is an essential and challenging task for autonomous driving. ...
Based on the above analysis, we present a class of lightweight feature pyramid network called Lite-FPN for keypoint-based monocular 3D object detectors. ...
arXiv:2105.00268v2
fatcat:5eovz5ygwngm3o2la3jpmgq6oa
CenterLoc3D: Monocular 3D Vehicle Localization Network for Roadside Surveillance Cameras
[article]
2022
arXiv
pre-print
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detection. ...
Most of the current monocular 3D vehicle detection methods leverage 2D detectors and additional geometric modules, which reduces the efficiency. ...
The authors would like to thank the researchers of Brno University of Technology for providing the public dataset BrnoCompSpeed which is used in our experiments. ...
arXiv:2203.14550v2
fatcat:3lroziztjzdi3gbzrw3wcv5pne
MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation
[article]
2021
arXiv
pre-print
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Monocular 3D object detection has recently shown promising results, however there remain challenging problems. ...
Little effort has been made to exploit the combination of heterogeneous 3D object datasets. ...
LiteFPN [44] proposes a generic Lite-FPN module that conducts multi-scale feature fusion for their keypoint-based detectors. ...
arXiv:2110.00464v1
fatcat:rjucapzkbvbbjaivveuujusgxm
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies
[article]
2020
arXiv
pre-print
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Due to the limited space, we focus the analysis on several key areas, i.e. 2D and 3D object detection in perception, depth estimation from cameras, multiple sensor fusion on the data, feature and task ...
A keypoint FPN-based method, called RTM3D [146] , predicts the nine perspective keypoints of a 3D bounding box in image space, and then utilize the geometric relationship of 3D and 2D perspectives to ...
LIDAR-BASED 3-D OBJECT DETECTION METHODS
PIXOR (ORiented 3D object detection from PIXel-wise NN
predictions)
TABLE II II .
CAMERA-BASED 3-D OBJECT DETECTION METHODS
Mousavian et al.' ...
arXiv:2006.06091v3
fatcat:nhdgivmtrzcarp463xzqvnxlwq
Real-Time Object Navigation with Deep Neural Networks and Hierarchical Reinforcement Learning
2020
IEEE Access
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FIGURE 7 . 7 Keypoint detection and matching details in noisy images: a -for CDXSLAM method, b -for OpenVSLAM method FIGURE 8. ...
On the one hand, they make it possible to generate more reliable descriptors for keypoints and images on the scenes for which they were trained, and thereby perform better point matching and loop detection ...
The research thesis is the methods and algorithms for the automatic determination of subgoals in a reinforcement learning problem for robotic systems. ...
doi:10.1109/access.2020.3034524
fatcat:cr5dettuijasdctw77pha7phne
AMMDAS: Multi-Modular Generative Masks Processing Architecture with Adaptive Wide Field-of-View Modeling Strategy
2020
IEEE Access
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Our current methodology considers only 2D (w, h) object coordinates during stage-2, so plan to implement object detection in 3D (l, w, h) coordinates [68] , [69] for stage-2. ...
These include the capacity to quickly identify ROI in an image, classify identified regions based on shape, and track detected pedestrians in 3D-real world coordinates. ...
doi:10.1109/access.2020.3033537
fatcat:hc4w6svannfzhafswgakb7ge2a
A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles
2020
Journal of Imaging
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on RGB-based object detection. ...
This survey presents recent advancements in 2D object detection for the case of UAVs, focusing on the differences, strategies, and trade-offs between the generic problem of object detection, and the adaptation ...
Real-time obstacle detection and avoidance system based on monocular views has been proposed in [89] . ...
doi:10.3390/jimaging6080078
pmid:34460693
pmcid:PMC8321148
fatcat:ds4kpheadvg6xp2fambrp6nffq
Learning Neural Textual Representations for Citation Recommendation
2021
2020 25th International Conference on Pattern Recognition (ICPR)
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-Jan 12, 2021
Wang, Ya; Zell, Andreas
1286
Yolo+FPN: 2D and 3D Fused Object Detection with an RGB-D
Camera
DAY 1 -Jan 12, 2021
Rotondo, Tiziana; Farinella,
Giovanni Maria; Giacalone,
Davide; ...
Monocular
Depth Estimation
DAY 4 -Jan 15, 2021
Chen, Yanxian; Ma, Huimin; Li, Xi;
Luo, Xiong
1413
S-VoteNet: Deep Hough Voting with Spherical Proposal for 3D
Object Detection
DAY 4 -Jan 15 ...
doi:10.1109/icpr48806.2021.9412725
fatcat:3vge2tpd2zf7jcv5btcixnaikm
3D Object Detection for Advanced Driver Assistance Systems
2021
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Extensive experiments on the KITTI 3D object detection benchmark demonstrate the validity of the proposed fusion scheme. ...
In this thesis, we develop a fast and accurate 3D object detector that converts raw point clouds collected by LiDARs into sparse occupancy cuboids to detect cars and other road users using deep convolutional ...
Well-classified (Easy) Examples
3D Object Detectors Based on the modality in use, 3D object detectors can be grouped into three main categories: 3D Object Detection from Point Cloud, 3D Object Detection ...
doi:10.20381/ruor-26565
fatcat:yj6g5h3v3zd5lkooxtqvae2j3y