Papers with Code 아카이브

6D Pose Estimation using RGBD

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하위 태스크: 0
평가표: 8
보존된 평가 기록: 35

Image: Zeng et al

코드

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

https://github.com/DC1991/FS-Net

공식 코드

FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism

https://github.com/DLR-RM/3DObjectTracking/tree/master/Mb-ICG

공식 코드

A Multi-body Tracking Framework -- From Rigid Objects to Kinematic Structures

https://github.com/DLR-RM/AugmentedAutoencoder

공식 코드

Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

https://github.com/Gorilla-Lab-SCUT/DualPoseNet

공식 코드

DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency

https://github.com/NVlabs/BundleSDF

공식 코드

BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects

https://github.com/UZ-SLAMLab/DrunkardsOdometry

공식 코드

The Drunkard's Odometry: Estimating Camera Motion in Deforming Scenes

https://github.com/aaronwool/rcvpose

공식 코드

Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting

https://github.com/ahundt/costar_dataset

공식 코드

The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints

https://github.com/ahundt/enas

공식 코드

The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints

https://github.com/andyzeng/apc-vision-toolbox

공식 코드

Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge

https://github.com/augcog/dttd2

공식 코드

Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset

https://github.com/augcog/robust-digital-twin-tracking

공식 코드

Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset

https://github.com/dlr-rm/3dobjecttracking

공식 코드

Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects

https://github.com/ethnhe/PVN3D

공식 코드

PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation

https://github.com/hughw19/NOCS_CVPR2019

공식 코드

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/j96w/6-PACK

공식 코드

6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints

https://github.com/jhu-lcsr/costar_plan

공식 코드

The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints

https://github.com/kroglice/MaskedFusion

공식 코드

MaskedFusion: Mask-based 6D Object Pose Estimation

https://github.com/lolrudy/gpv_pose

공식 코드

GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting

https://github.com/qq456cvb/cppf

공식 코드

CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild

https://github.com/thodan/bop_toolkit

공식 코드

BOP: Benchmark for 6D Object Pose Estimation

https://github.com/thodan/epos

공식 코드

EPOS: Estimating 6D Pose of Objects with Symmetries

https://github.com/wenbowen123/BundleTrack

공식 코드

BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models

https://github.com/wenbowen123/icra20-hand-object-pose

공식 코드

Robust, Occlusion-aware Pose Estimation for Objects Grasped by Adaptive Hands

https://github.com/zju3dv/gcasp

공식 코드

Generative Category-Level Shape and Pose Estimation with Semantic Primitives

https://github.com/zubair-irshad/shapo

공식 코드

ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization

https://github.com/DC1991/FS_Net

FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism

https://github.com/DLR-RM/BlenderProc

BOP Challenge 2020 on 6D Object Localization

https://github.com/NVlabs/PoseCNN-PyTorch

PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

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/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/augcog/dttdv1

Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset

https://github.com/azad96/cosypose-custom

BOP Challenge 2020 on 6D Object Localization

https://github.com/caoquan95/6D-pose-project

PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

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