Papers with Code 아카이브

Vehicle Pose Estimation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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평가표

4

보존된 평가 기록

22

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Banconxuan/RTM3D

공식 코드

RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving

https://github.com/HMX2013/Covex-hull-based-fitting-3D-LiDAR-ROS

공식 코드

An Efficient Convex Hull-based Vehicle Pose Estimation Method for 3D LiDAR

https://github.com/JakubSochor/BoxCars

공식 코드

BoxCars: Improving Fine-Grained Recognition of Vehicles using 3-D Bounding Boxes in Traffic Surveillance

https://github.com/Nicholasli1995/EgoNet

공식 코드

Exploring intermediate representation for monocular vehicle pose estimation

https://github.com/chenyilun95/DSGN

공식 코드

DSGN: Deep Stereo Geometry Network for 3D Object Detection

https://github.com/dingmyu/D4LCN

공식 코드

Learning Depth-Guided Convolutions for Monocular 3D Object Detection

https://github.com/garrickbrazil/M3D-RPN

공식 코드

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/lkeab/gsnet

공식 코드

GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision

https://github.com/matanr/capex

공식 코드

CapeX: Category-Agnostic Pose Estimation from Textual Point Explanation

https://github.com/mit-spark/pace

공식 코드

Optimal and Robust Category-level Perception: Object Pose and Shape Estimation from 2D and 3D Semantic Keypoints

https://github.com/orhir/PoseAnything

공식 코드

A Graph-Based Approach for Category-Agnostic Pose Estimation

https://github.com/zju3dv/disprcnn

공식 코드

Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation

https://github.com/Chenzixi1/D4LCNpaddle

Learning Depth-Guided Convolutions for Monocular 3D Object Detection

https://github.com/ConnorChristie/image-to-3d-bbox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/JuliaChae/M3D-RPN-Waymo

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/ZhixinLai/3D-detection-with-monocular-RGB-image

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/abhi1kumar/M3D-RPN

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/cersar/3D_detection

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/dineshreddy91/Occlusion_Net

https://github.com/fuenwang/3D-BoundingBox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/garrickbrazil/kinematic3d

Kinematic 3D Object Detection in Monocular Video

https://github.com/lzccccc/3d-bounding-box-estimation-for-autonomous-driving

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/m-parchami/3DVehicleDetection

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/maudzung/RTM3D

RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving

https://github.com/orhir/EdgeCape

A Graph-Based Approach for Category-Agnostic Pose Estimation

https://github.com/ruhyadi/YOLO3D

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/ruhyadi/yolo3d-lightning

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/skhadem/3D-BoundingBox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/smallcorgi/3D-Deepbox

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/wittmaan/a2d2

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/xiaohaoChen/rrc_detection

Subcategory-aware Convolutional Neural Networks for Object Proposals and Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.