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Lite-FPN for Keypoint-based Monocular 3D Object Detection [article]

Lei Yang, Xinyu Zhang, Li Wang, Minghan Zhu, Jun Li
2021 arXiv   pre-print
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]

Tang Xinyao and Song Huansheng and Wang Wei and Zhao Chunhui
2022 arXiv   pre-print
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]

Jonas Heylen, Mark De Wolf, Bruno Dawagne, Marc Proesmans, Luc Van Gool, Wim Abbeloos, Hazem Abdelkawy, Daniel Olmeda Reino
2021 arXiv   pre-print
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]

Yu Huang, Yue Chen
2020 arXiv   pre-print
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

Aleksey Staroverov, Dmitry A. Yudin, Ilya Belkin, Vasily Adeshkin, Yaroslav K. Solomentsev, Aleksandr I. Panov
2020 IEEE Access  
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

Venkata Subbaiah Desanamukula, Premith Kumar Chilukuri, Pushkal Padala, Preethi Padala, Prasad Reddy Pvgd
2020 IEEE Access  
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

Dario Cazzato, Claudio Cimarelli, Jose Luis Sanchez-Lopez, Holger Voos, Marco Leo
2020 Journal of Imaging  
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

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
-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

Selameab Demilew, University, My
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