Detection and pose estimation of texture-less objects still faces several challenges such as
foreground occlusions, background clutter, multi-instance objects, large scale and pose …

Detection and pose estimation of texture-less objects still faces several challenges such as
foreground occlusions, background clutter, multi-instance objects, large scale and pose …

This paper introduces an improved algorithm for texture-less object detection and pose
estimation in industrial scenes. In the template training stage, a multi-scale template training …

3-D pose estimation for texture-less objects remains a challenging problem. Previous works
either focus on a template matching method to find the nearest template as a candidate, or …

The 6D (6 Degree of freedom) pose estimation (or pose measurement) of machined
reflective texture-less objects, which are common in industry, is a significant but challenging …

This paper addresses the challenge of detecting and localizing a poorly textured known
object, by initially estimating its complete 3D pose in a video sequence. Our solution relies …

This paper addresses the problems of object detection and 6 DoF pose estimation from a
sequence of RGB images. Our deep learning-based approach uses only synthetic non …

Local patch-based methods of object detection and pose estimation are promising.
However, to the best of the authors' knowledge, traditional red-green-blue and depth (RGB …

We present a method that can recognize new objects and estimate their 3D pose in RGB
images even under partial occlusions. Our method requires neither a training phase on …

We propose a framework for automatic modeling, detection, and tracking of 3D objects with
a Kinect. The detection part is mainly based on the recent template-based LINEMOD …