6D Pose Estimation using RGB
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6D Pose Estimation using RGB refers to the task of determining the six degree-of-freedom (6D) pose of an object in 3D space based on RGB images. This involves estimating the position and orientation of an object in a scene, and is a fundamental problem in computer vision and robotics. In this task, the goal is to estimate the 6D pose of an object given an RGB image of the object and the scene, which can be used for tasks such as robotic manipulation, augmented reality, and scene reconstruction.
<span style="color:grey; opacity: 0.6">( Image credit: Segmentation-driven 6D Object Pose Estimation )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yegyu-han/senseshift6d
공식 코드https://github.com/zakharos/DPOD
공식 코드https://github.com/zhujunli1993/swindepose
공식 코드Depth-based 6DoF Object Pose Estimation using Swin Transformer
https://github.com/zitronian/6dposediffusion
공식 코드Particle-based 6D Object Pose Estimation from Point Clouds using Diffusion Models
https://github.com/zray26/dr-pose
공식 코드https://github.com/2023-MindSpore-1/ms-code-9/tree/main/PVNet
https://github.com/AP-EPFL/DA-segmentation-driven-pose
Estimating 6D Pose From Localizing Designated Surface Keypoints
https://github.com/DC1991/FS_Net
https://github.com/DLR-RM/BlenderProc
https://github.com/GH3927/Pix2Pix-applied-to-cranes
Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation
https://github.com/Microsoft/singleshotpose
https://github.com/MindSpore-paper-code-3/code9/tree/main/PVNet
https://github.com/NVlabs/PoseCNN-PyTorch
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/NVlabs/latentfusion
https://github.com/RiplleYang/DenseFusion
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/Theopetitjean/DenseFusion_R_Invariant
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/Yongjjun/singleshotpose
https://github.com/Yotonctu/densefusion_torch1.0
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/YuhangMing/Object-Guided-Relocalisation
Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation
https://github.com/a2824256/singleshotpose_imp
https://github.com/azad96/cosypose-custom
CosyPose: Consistent multi-view multi-object 6D pose estimation
https://github.com/caoquan95/6D-pose-project
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/chronoshell/copyydscsv
HybridPose: 6D Object Pose Estimation under Hybrid Representations
https://github.com/cviviers/YOLOv5-6D-Pose
https://github.com/cvlab-epfl/wide-depth-range-pose
https://github.com/cxt98/Densefusion-transparency
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/edavalosanaya/FastPoseCNN
https://github.com/gidobot/SilhoNet
https://github.com/hz-ants/DenseFusion
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/hz-ants/HybridPose
HybridPose: 6D Object Pose Estimation under Hybrid Representations
https://github.com/hz-ants/Pix2Pose
Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation
https://github.com/hz-ants/Posecnn
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/hz-ants/SilhoNet
https://github.com/hz-ants/betapose
Estimating 6D Pose From Localizing Designated Surface Keypoints
https://github.com/hz-ants/cosypose-Base-on-multi-view
CosyPose: Consistent multi-view multi-object 6D pose estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.