Papers with Code 아카이브
6D Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 6
- 보존된 평가 기록
- 27
Image: Zeng et al
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zakharos/DPOD
공식 코드https://github.com/zerchen/AlignSDF
공식 코드AlignSDF: Pose-Aligned Signed Distance Fields for Hand-Object Reconstruction
https://github.com/zerchen/gSDF
공식 코드gSDF: Geometry-Driven Signed Distance Functions for 3D Hand-Object Reconstruction
https://github.com/zhanhz/krf
공식 코드PCKRF: Point Cloud Completion and Keypoint Refinement With Fusion Data for 6D Pose Estimation
https://github.com/zhujunli1993/swindepose
공식 코드Depth-based 6DoF Object Pose Estimation using Swin Transformer
https://github.com/zju3dv/OnePose
공식 코드https://github.com/zubair-irshad/shapo
공식 코드ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization
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/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/Wiqzard/PViT-6D
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/anilarmagan/HANDS19-Challenge-Toolbox
HOnnotate: A method for 3D Annotation of Hand and Object Poses
https://github.com/augcog/dttdv1
Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset
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/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
Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation
https://github.com/gidobot/SilhoNet
https://github.com/hassony2/manopth
Learning joint reconstruction of hands and manipulated objects
https://github.com/hassony2/obman
Learning joint reconstruction of hands and manipulated objects
https://github.com/hassony2/obman_train
Learning joint reconstruction of hands and manipulated objects
https://github.com/hz-ants/DenseFusion
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/hz-ants/FFB6D
PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation
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/apc-vision-toolbox
Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.