|
|
--- |
|
|
license: mit |
|
|
--- |
|
|
We provide our physically-based renderings of the YCB-V object dataset randomized YCB-V (YCB-V-RAND) with **randomized texture**, **randomized material**, and **randomized lighting**, allowing to benchmark the influence of such variations on the task of 2D object detection and 6DoF object pose estimation. For more details on the dataset, please take a look on our paper referenced below. |
|
|
|
|
|
 |
|
|
|
|
|
|
|
|
If you find our work useful, please consider citing our work. |
|
|
``` |
|
|
@inproceedings{pollabauer2024generalizing, |
|
|
title={Generalizing Neural Radiance Fields for Robust 6D Pose Estimation of Unseen Appearances}, |
|
|
author={P{\"o}llabauer, Thomas and Wirth, Tristan and Weitz, Paul and Knauthe, Volker and Kuijper, Arjan and Fellner, Dieter W}, |
|
|
booktitle={International Symposium on Visual Computing}, |
|
|
pages={300--314}, |
|
|
year={2024}, |
|
|
organization={Springer} |
|
|
} |
|
|
``` |
