Papers with Code 아카이브
3D Object Detection
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3D Object Detection is a task in computer vision where the goal is to identify and locate objects in a 3D environment based on their shape, location, and orientation. It involves detecting the presence of objects and determining their location in the 3D space in real-time. This task is crucial for applications such as autonomous vehicles, robotics, and augmented reality.
<span style="color:grey; opacity: 0.6">( Image credit: AVOD )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AtlasCoCo/Darknet
https://github.com/AutoVision-cloud/DeformablePVRCNN
Deformable PV-RCNN: Improving 3D Object Detection with Learned Deformations
https://github.com/BBuf/Darknet
https://github.com/BPMJG/annotated-F-pointnet
https://github.com/BPMJG/annotated_pointnet
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/Benzlxs/benzlxs.github.io
Three-dimensional Backbone Network for 3D Object Detection in Traffic Scenes
https://github.com/CahideSara/deneme
https://github.com/CarkusL/CenterPoint
https://github.com/Chamchis/AICCTV
https://github.com/Chenzixi1/D4LCNpaddle
Learning Depth-Guided Convolutions for Monocular 3D Object Detection
https://github.com/Cjmmmmmm/BreastUltrasound_Detection
https://github.com/Code-Fight/darknet_study
https://github.com/ConnorChristie/image-to-3d-bbox
https://github.com/CosmiQ/yolt
https://github.com/CuberrChen/VoxelNet
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
https://github.com/DInesh1234-wq/tyredataset
https://github.com/DavianYang/yolo.ai
https://github.com/Deeplodocus/COCO-with-YOLO
https://github.com/Discover304/MMDetection3D-Eloss
Exploring Data Augmentation for Multi-Modality 3D Object Detection
https://github.com/DonCorle0ne/damage_detection
https://github.com/Donvink/Car_Detection_for_Autonomous_Driving
https://github.com/EMsnap/RobotSorting
https://github.com/Eisbaer8/DeepGTAV
Precise Synthetic Image and LiDAR (PreSIL) Dataset for Autonomous Vehicle Perception
https://github.com/Ereebay/CV-Documents
https://github.com/Ereebay/Deep-Learning-Documents
https://github.com/Ereebay/DeepLearningDocuments
https://github.com/FMsunyh/keras-yolo2
https://github.com/FateScript/CenterNet-better
https://github.com/FlowWind1999/pointnet-2
https://github.com/Ggs1mida/Awesome-DataFusion
https://github.com/Ggs1mida/Awesome-PointCloudRegistration
https://github.com/GianRomani/YOLOv3-Neural-Networks-project-
https://github.com/Guanghan/CenterNet-Gluon
https://github.com/Guanghan/mxnet-centernet
https://github.com/HSRW-EMRP-WS1920-Drone/object_detection_and_landing
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.