[CVPR 2021] Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis (official pytorch implementation)
Official implementation of "Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis", CVPR 2021
Figure. Our proposed 3D point-based scene graph generation (SGGpoint) framework consisting of three sequential stages, namely, scene graph construction, reasoning, and inference.
A quick glance at some features of our cleaned 3DSSG-O27R16 dataset (compared to the original 3DSSG dataset):
more-comfortable-than
) filtered out - we focus on structural relationships instead;To obtain our preprocessed 3DSSG-O27R16 dataset, please follow the instructions in our project page - or you could also derive these preprocessed data yourselves by following this step-by-step preprocessing guidance with scripts provided.
This repo. also contains Pytorch implementation of the following modules:
If you find our data or project useful in your research, please cite:
@InProceedings{SGGpoint,
author = {Zhang, Chaoyi and Yu, Jianhui and Song, Yang and Cai, Weidong},
title = {Exploiting Edge-Oriented Reasoning for 3D Point-Based Scene Graph Analysis},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2021},
pages = {9705-9715}
}