
FocalPose++ is a novel method that accurately estimates both camera focal length and object pose from a single RGB image by extending the render-and-compare approach with focal length update rules, a disentangled training loss, and a synthetic data generation strategy based on real data distributions.


coremsg

focalpose-estimating-camera-focal-length-and-object-pose-from-a-single-image-using-a-render-and-compare-approach


FocalPose++: Estimating Camera Focal Length and Object Pose from a Single Image Using a Render-and-Compare Approach


title_rewrite


The proposed TransPose framework exploits Transformer Encoder with a geometry-aware module to develop better learning of point cloud feature representations for accurate 6D object pose estimation.


transpose-6d-object-pose-estimation-with-geometry-aware-transformer


TransPose: 6D Object Pose Estimation with Geometry-Aware Transformer



Proposing SD-Net for accurate 6D pose estimation in bin-picking scenarios through symmetric-aware keypoint prediction and domain adaptation.


sd-net-symmetric-aware-keypoint-prediction-and-domain-adaptation-for-6d-pose-estimation-in-bin-picking-scenarios


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