38 citations · 79 across the 9 of their papers we have counts for
9 papers
A Review on Object Pose Recovery: from 3D Bounding Box Detectors to Full 6D Pose Estimators
Caner Sahin, Guillermo Garcia-Hernando, Juil Sock +1
Object pose recovery has gained increasing attention in the computer vision field as it has become an important problem in rapidly evolving technological areas related to autonomou…
Instance- and Category-level 6D Object Pose Estimation
Caner Sahin, Guillermo Garcia-Hernando, Juil Sock +1
6D object pose estimation is an important task that determines the 3D position and 3D rotation of an object in camera-centred coordinates. By utilizing such a task, one can propose…
A Summary of the 4th International Workshop on Recovering 6D Object Pose
Tomas Hodan, Rigas Kouskouridas, Tae-Kyun Kim +12
This document summarizes the 4th International Workshop on Recovering 6D Object Pose which was organized in conjunction with ECCV 2018 in Munich. The workshop featured four invited…
BOP: Benchmark for 6D Object Pose Estimation
Tomas Hodan, Frank Michel, Eric Brachmann +13
We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the obj…
Category-level 6D Object Pose Recovery in Depth Images
Caner Sahin, Tae-Kyun Kim
Intra-class variations, distribution shifts among source and target domains are the major challenges of category-level tasks. In this study, we address category-level full 6D objec…
Multi-Task Deep Networks for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios
Juil Sock, Kwang In Kim, Caner Sahin +1
In bin-picking scenarios, multiple instances of an object of interest are stacked in a pile randomly, and hence, the instances are inherently subjected to the challenges: severe oc…
Recovering 6D Object Pose: A Review and Multi-modal Analysis
Caner Sahin, Tae-Kyun Kim
A large number of studies analyse object detection and pose estimation at visual level in 2D, discussing the effects of challenges such as occlusion, clutter, texture, etc., on the…
A Learning-based Variable Size Part Extraction Architecture for 6D Object Pose Recovery in Depth
Caner Sahin, Rigas Kouskouridas, Tae-Kyun Kim
State-of-the-art techniques for 6D object pose recovery depend on occlusion-free point clouds to accurately register objects in 3D space. To deal with this shortcoming, we introduc…
Iterative Hough Forest with Histogram of Control Points for 6 DoF Object Registration from Depth Images
Caner Sahin, Rigas Kouskouridas, Tae-Kyun Kim
State-of-the-art techniques proposed for 6D object pose recovery depend on occlusion-free point clouds to accurately register objects in 3D space. To reduce this dependency, we int…