We present the evaluation methodology, datasets and results of the BOP Challenge 2022,
the fourth in a series of public competitions organized with the goal to capture the status quo …

This paper presents the evaluation methodology, datasets, and results of the BOP
Challenge 2020, the third in a series of public competitions organized with the goal to …

Transparent object perception is a rapidly develo** research problem in artificial
intelligence. The ability to perceive transparent objects enables robots to achieve higher …

This paper presents a critical analysis of image-based 3D reconstruction using neural
radiance fields (NeRFs), with a focus on quantitative comparisons with respect to traditional …

We present the evaluation methodology datasets and results of the BOP Challenge 2023 the
fifth in a series of public com-petitions organized to capture the state of the art in model …

In the field of industrial metrology, there is a rising need for 3D information at a very high
resolution for micro-measurements and quality control of transparent objects such as glass …

Majority of the perception methods in robotics require depth information provided by RGB-D
cameras. However, standard 3D sensors fail to capture depth of transparent objects due to …

Recovering the 3D shape of transparent objects using a small number of unconstrained
natural images is an ill-posed problem. Complex light paths induced by refraction and …

We propose NEMTO, the first end-to-end neural rendering pipeline to model 3D transparent
objects with complex geometry and unknown indices of refraction. Commonly used …

Summary A three‐dimensional (3D) reconstruction method of structured light based on
photoelastic fringes was proposed in this research. The photoelastic fringes are produced by …