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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 111–120 of 233 papers

TitleStatusHype
6D-Diff: A Keypoint Diffusion Framework for 6D Object Pose Estimation—0
Three-Filters-to-Normal+: Revisiting Discontinuity Discrimination in Depth-to-Normal Translation—0
Synthetic Data Generation for Bridging Sim2Real Gap in a Production Environment—0
Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile SensorsCode0
TransPose: 6D Object Pose Estimation with Geometry-Aware Transformer—0
ZS6D: Zero-shot 6D Object Pose Estimation using Vision Transformers—0
Exploiting Point-Wise Attention in 6D Object Pose Estimation Based on Bidirectional Prediction—0
Challenges for Monocular 6D Object Pose Estimation in Robotics—0
YOLOPose V2: Understanding and Improving Transformer-based 6D Pose Estimation—0
TransPose: A Transformer-based 6D Object Pose Estimation Network with Depth Refinement—0
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