Papers with Code 아카이브

6D Pose Estimation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

2

평가표

6

보존된 평가 기록

27

코드

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

https://github.com/deepmind/threednel

공식 코드

3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose Estimation

https://github.com/dingthuang/sd-net

공식 코드

SD-Net: Symmetric-Aware Keypoint Prediction and Domain Adaptation for 6D Pose Estimation In Bin-picking Scenarios

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/dubiouscactus/meta-learning-hope

공식 코드

A new benchmark for group distribution shifts in hand grasp regression for object manipulation. Can meta-learning raise the bar?

https://github.com/elego9/6dp-data-bias

공식 코드

Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation

https://github.com/ethnhe/FFB6D

공식 코드

FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation

https://github.com/ethnhe/FS6D-PyTorch

공식 코드

FS6D: Few-Shot 6D Pose Estimation of Novel Objects

https://github.com/ethnhe/PVN3D

공식 코드

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

https://github.com/fraunhoferhhi/casapose

공식 코드

CASAPose: Class-Adaptive and Semantic-Aware Multi-Object Pose Estimation

https://github.com/fraunhoferhhi/spvloc

공식 코드

SPVLoc: Semantic Panoramic Viewport Matching for 6D Camera Localization in Unseen Environments

https://github.com/fulliu/lc

공식 코드

Linear-Covariance Loss for End-to-End Learning of 6D Pose Estimation

https://github.com/fylwen/disp-6d

공식 코드

DISP6D: Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimation

https://github.com/gajdosech2/bin-detect

공식 코드

Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans

https://github.com/ganwanshui/es6d

공식 코드

ES6D: A Computation Efficient and Symmetry-Aware 6D Pose Regression Framework

https://github.com/gorilla-lab-scut/bico-net

공식 코드

BiCo-Net: Regress Globally, Match Locally for Robust 6D Pose Estimation

https://github.com/gorilla-lab-scut/dcl-net

공식 코드

DCL-Net: Deep Correspondence Learning Network for 6D Pose Estimation

https://github.com/gorilla-lab-scut/mast

공식 코드

Manifold-Aware Self-Training for Unsupervised Domain Adaptation on Regressing 6D Object Pose

https://github.com/gorilla-lab-scut/ss-conv

공식 코드

Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space

https://github.com/greatenanoymous/rgbtrack

공식 코드

RGBTrack: Fast, Robust Depth-Free 6D Pose Estimation and Tracking

https://github.com/hassony2/homan

공식 코드

Towards unconstrained joint hand-object reconstruction from RGB videos

https://github.com/hoenigpeter/randomized_texturing

공식 코드

Shape-biased Texture Agnostic Representations for Improved Textureless and Metallic Object Detection and 6D Pose Estimation

https://github.com/hp-cao/6impose

공식 코드

6IMPOSE: Bridging the Reality Gap in 6D Pose Estimation for Robotic Grasping

https://github.com/hughw19/NOCS_CVPR2019

공식 코드

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

https://github.com/imitrob/imitrob_dataset_code

공식 코드

Imitrob: Imitation Learning Dataset for Training and Evaluating 6D Object Pose Estimators

https://github.com/interactivegl/vision6d

공식 코드

Vision6D: 3D-to-2D Interactive Visualization and Annotation Tool for 6D Pose Estimation

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

공식 코드

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

https://github.com/jcorsetti/fcgf6d

공식 코드

Revisiting Fully Convolutional Geometric Features for Object 6D Pose Estimation

https://github.com/jhacsonmeza/MarkerPose

공식 코드

MarkerPose: Robust Real-time Planar Target Tracking for Accurate Stereo Pose Estimation

https://github.com/jiehonglin/self-dpdn

공식 코드

Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networks

https://github.com/junggy/housecat6d

공식 코드

HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios

https://github.com/jzhao12/cvam-pose

공식 코드

CVAM-Pose: Conditional Variational Autoencoder for Multi-Object Monocular Pose Estimation

https://github.com/kirumang/NOL

공식 코드

Neural Object Learning for 6D Pose Estimation Using a Few Cluttered Images

https://github.com/kroglice/MaskedFusion

공식 코드

MaskedFusion: Mask-based 6D Object Pose Estimation

https://github.com/kywind/self-corr-pose

공식 코드

Self-Supervised Geometric Correspondence for Category-Level 6D Object Pose Estimation in the Wild

https://github.com/leolyliu/teg-track

공식 코드

Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing

https://github.com/lixiny/artiboost

공식 코드

ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis

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