SGGpoint
[CVPR 2021] Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis (official pytorch implementation)
Install / Use
/learn @chaoyivision/SGGpointREADME
SGGpoint
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 (SGG<sub>point</sub>) framework consisting of three sequential stages, namely, scene graph construction, reasoning, and inference.
Dataset
A quick glance at some features of our cleaned <b>3DSSG-<font color="red">O27</font><font color="blue">R16</font></b> dataset (compared to the original 3DSSG dataset):
- dense point cloud representation with color and normal vector info. encoded - see Sec. A - Point Cloud Sampling;
- with same scene-level split applied on 3DSSG - but with <i>FullScenes (i.e., original graphs)</i> instead of SubScenes (subgraphs of 4-9 nodes in 3DSSG);
- with small / partial scenes of low quality excluded - see this list (officially announced in 3DSSG's FAQ Page);
- with object-level class imbalance alleviated - see Sec. B1 - Node (object) Remapping;
- with edge-wise comparative relationships (e.g.,
more-comfortable-than) filtered out - we focus on <i>structural relationships</i> instead; - reformulate the edge predictions from a multi-label classification problem to a multi-class one - see Sec. B2 - Edge (Relationship) Relabelling;
To obtain our preprocessed <b>3DSSG-<font color="red">O27</font><font color="blue">R16</font></b> 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.
Code
This repo. also contains Pytorch implementation of the following modules:
- [x] Preprocessing A: 10dimPoints & batch script;
- [x] Preprocessing B: SceneGraphAnnotation.json & Prep. Script;
- [x] dataloader's instructions (might be updated later here);
- [x] SubNetworks.py: Backbones (PointNet & DGCNN), Tails (NodeMLP & EdgeMLP), edge feats. initialization func.;
- [x] EdgeGCN.py: CoreNetwork with two twinning attentions;
Citation
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}
}
Related Skills
node-connect
351.2kDiagnose OpenClaw node connection and pairing failures for Android, iOS, and macOS companion apps
frontend-design
110.6kCreate distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
openai-whisper-api
351.2kTranscribe audio via OpenAI Audio Transcriptions API (Whisper).
qqbot-media
351.2kQQBot 富媒体收发能力。使用 <qqmedia> 标签,系统根据文件扩展名自动识别类型(图片/语音/视频/文件)。
