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6D Pose Estimation using RGB

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.

( Image credit: Segmentation-driven 6D Object Pose Estimation )

Papers

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Showing 61–70 of 233 papers

TitleStatusHype
HybridPose: 6D Object Pose Estimation under Hybrid RepresentationsCode1
Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-PickingCode1
CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose EstimationCode1
Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size EstimationCode1
PVNet: Pixel-wise Voting Network for 6DoF Pose EstimationCode1
BOP: Benchmark for 6D Object Pose EstimationCode1
DeepIM: Deep Iterative Matching for 6D Pose EstimationCode1
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered ScenesCode1
T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less ObjectsCode1
SenseShift6D: Multimodal RGB-D Benchmarking for Robust 6D Pose Estimation across Environment and Sensor VariationsCode0
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