Pose Guided RGBD Feature Learning for 3D Object Pose Estimation

no code implementations • ICCV 2017 • Vassileios Balntas, Andreas Doumanoglou, Caner Sahin, Juil Sock, Rigas Kouskouridas, Tae-Kyun Kim

In this paper we examine the effects of using object poses as guidance to learning robust features for 3D object pose estimation.

Feature Correlation Metric Learning +2

Siamese Regression Networks with Efficient mid-level Feature Extraction for 3D Object Pose Estimation

no code implementations • 8 Jul 2016 • Andreas Doumanoglou, Vassileios Balntas, Rigas Kouskouridas, Tae-Kyun Kim

Furthermore, we argue that our pose-guided feature learning using our Siamese Regression Network generates more discriminative features that outperform the state of the art.

3D Pose Estimation Object +1

Latent-Class Hough Forests for 6 DoF Object Pose Estimation

no code implementations • 3 Feb 2016 • Rigas Kouskouridas, Alykhan Tejani, Andreas Doumanoglou, Danhang Tang, Tae-Kyun Kim

In this paper we present Latent-Class Hough Forests, a method for object detection and 6 DoF pose estimation in heavily cluttered and occluded scenarios.

object-detection Object Detection +2

Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd

no code implementations • CVPR 2016 • Andreas Doumanoglou, Rigas Kouskouridas, Sotiris Malassiotis, Tae-Kyun Kim

In this work, we present a complete framework for both single shot-based 6D object pose estimation and next-best-view prediction based on Hough Forests, the state of the art object pose estimator that performs classification and regression jointly.

6D Pose Estimation 6D Pose Estimation using RGB +4