Making Deep Heatmaps Robust to Partial Occlusions for 3D Object Pose Estimation

This publication has 28 references indexed in Scilit:

• PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
  2018
• Real-Time Seamless Single Shot 6D Object Pose Prediction
  2018
• SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again
  2017
• BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth
  2017
• Robust 3D Object Tracking from Monocular Images Using Stable Parts
  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
• 6-DoF object pose from semantic keypoints
  2017
• Yale-CMU-Berkeley dataset for robotic manipulation research
  The International Journal of Robotics Research, 2017
• Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image
  2016
• Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images
  2015
• Distinctive Image Features from Scale-Invariant Keypoints
  International Journal of Computer Vision, 2004