HAIS_2GNN: 3D Visual Grounding with Graph and Attention

Overview

HAIS_2GNN: 3D Visual Grounding with Graph and Attention

This repository is for the HAIS_2GNN research project.

Tao Gu, Yue Chen

Introduction

The motivation of this project is to improve the accuracy of 3D visual grounding. In this report, we propose a new model, named HAIS_2GNN based on the InstanceRefer model, to tackle the problem of insufficient connections between instance proposals. Our model incorporates a powerful instance segmentation model HAIS and strengthens the instance features by the structure of graph and attention, so that the text and point cloud can be better matched together. Experiments confirm that our method outperforms the InstanceRefer on ScanRefer validation datasets. Link to the technical report

Setup

The code is tested on Ubuntu 20.04.3 LTS with Python 3.9.7 PyTorch 1.10.1 CUDA 11.3.1 installed.

conda install pytorch==1.10.1 torchvision==0.11.2 cudatoolkit=11.3 -c pytorch

Install the necessary packages listed out in requirements.txt:

pip install -r requirements.txt

After all packages are properly installed, please run the following commands to compile the torchsaprse v1.4.0:

sudo apt-get install libsparsehash-dev
pip install --upgrade git+https://github.com/mit-han-lab/[email protected]

Before moving on to the next step, please don't forget to set the project root path to the CONF.PATH.BASE in lib/config.py.

Data preparation

  1. Download the ScanRefer dataset and unzip it under data/.
  2. Downloadand the preprocessed GLoVE embeddings (~990MB) and put them under data/.
  3. Download the ScanNetV2 dataset and put (or link) scans/ under (or to) data/scannet/scans/ (Please follow the ScanNet Instructions for downloading the ScanNet dataset). After this step, there should be folders containing the ScanNet scene data under the data/scannet/scans/ with names like scene0000_00
  4. Used official and pre-trained HAIS generate panoptic segmentation in PointGroupInst/. We will provide the pre-trained data soon.
  5. Pre-processed instance labels, and new data should be generated in data/scannet/pointgroup_data/
cd data/scannet/
python prepare_data.py --split train --pointgroupinst_path [YOUR_PATH]
python prepare_data.py --split val   --pointgroupinst_path [YOUR_PATH]
python prepare_data.py --split test  --pointgroupinst_path [YOUR_PATH]

Finally, the dataset folder should be organized as follows.

InstanceRefer
├── data
│   ├── glove.p
│   ├── ScanRefer_filtered.json
│   ├── ...
│   ├── scannet
│   │  ├── meta_data
│   │  ├── pointgroup_data
│   │  │  ├── scene0000_00_aligned_bbox.npy
│   │  │  ├── scene0000_00_aligned_vert.npy
│   │  ├──├──  ... ...

Training

Train the InstanceRefer model. You can change hyper-parameters in config/InstanceRefer.yaml:

python scripts/train.py --log_dir HAIS_2GNN

Evaluation

You need specific the use_checkpoint with the folder that contains model.pth in config/InstanceRefer.yaml and run with:

python scripts/eval.py

Pre-trained Models

Input [email protected] Unique [email protected] Checkpoints
xyz+rgb 39.24 33.66 will be released soon

TODO

  • Add pre-trained HAIS dataset.
  • Release pre-trained model.
  • Merge HAIS in an end-to-end manner.
  • Upload to ScanRefer benchmark

Changelog

02/09/2022: Released HAIS_2GNN

Acknowledgement

This work is a research project conducted by Tao Gu and Yue Chen for ADL4CV:Visual Computing course at the Technical University of Munich.

We acknowledge that our work is based on ScanRefer, InstanceRefer, HAIS, torchsaprse, and pytorch_geometric.

License

This repository is released under MIT License (see LICENSE file for details).

Owner
Yue Chen
Yue Chen
Datasets of Automatic Keyphrase Extraction

This repository contains 20 annotated datasets of Automatic Keyphrase Extraction made available by the research community. Following are the datasets and the original papers that proposed them. If yo

LIAAD - Laboratory of Artificial Intelligence and Decision Support 163 Dec 23, 2022
pyupbit 라이브러리를 활용하여 upbit에서 비트코인을 자동매매하는 코드입니다. 조코딩 유튜브 채널에서 자세한 강의 영상을 보실 수 있습니다.

파이썬 비트코인 투자 자동화 강의 코드 by 유튜브 조코딩 채널 pyupbit 라이브러리를 활용하여 upbit 거래소에서 비트코인 자동매매를 하는 코드입니다. 파일 구성 test.py : 잔고 조회 (1강) backtest.py : 백테스팅 코드 (2강) bestK.p

조코딩 JoCoding 186 Dec 29, 2022
This is the 25 + 1 year anniversary version of the 1995 Rachford-Rice contest

Rachford-Rice Contest This is the 25 + 1 year anniversary version of the 1995 Rachford-Rice contest. Can you solve the Rachford-Rice problem for all t

13 Sep 20, 2022
Training RNNs as Fast as CNNs

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which

Tao Lei 14 Dec 12, 2022
Finetune gpt-2 in google colab

gpt-2-colab finetune gpt-2 in google colab sample result (117M) from retraining on A Tale of Two Cities by Charles Di

212 Jan 02, 2023
Need: Image Search With Python

Need: Image Search The problem is that a user needs to search for a specific ima

Surya Komandooru 1 Dec 30, 2021
Indobenchmark are collections of Natural Language Understanding (IndoNLU) and Natural Language Generation (IndoNLG)

Indobenchmark Toolkit Indobenchmark are collections of Natural Language Understanding (IndoNLU) and Natural Language Generation (IndoNLG) resources fo

Samuel Cahyawijaya 11 Aug 26, 2022
Material for GW4SHM workshop, 16/03/2022.

GW4SHM Workshop Wednesday, 16th March 2022 (13:00 – 15:15 GMT): Presented by: Dr. Rhodri Nelson, Imperial College London Project website: https://www.

Devito Codes 1 Mar 16, 2022
基于pytorch_rnn的古诗词生成

pytorch_peot_rnn 基于pytorch_rnn的古诗词生成 说明 config.py里面含有训练、测试、预测的参数,更改后运行: python main.py 预测结果 if config.do_predict: result = trainer.generate('丽日照残春')

西西嘛呦 3 May 26, 2022
LSTC: Boosting Atomic Action Detection with Long-Short-Term Context

LSTC: Boosting Atomic Action Detection with Long-Short-Term Context This Repository contains the code on AVA of our ACM MM 2021 paper: LSTC: Boosting

Tencent YouTu Research 9 Oct 11, 2022
XLNet: Generalized Autoregressive Pretraining for Language Understanding

Introduction XLNet is a new unsupervised language representation learning method based on a novel generalized permutation language modeling objective.

Zihang Dai 6k Jan 07, 2023
An assignment on creating a minimalist neural network toolkit for CS11-747

minnn by Graham Neubig, Zhisong Zhang, and Divyansh Kaushik This is an exercise in developing a minimalist neural network toolkit for NLP, part of Car

Graham Neubig 63 Dec 29, 2022
Facilitating the design, comparison and sharing of deep text matching models.

MatchZoo Facilitating the design, comparison and sharing of deep text matching models. MatchZoo 是一个通用的文本匹配工具包,它旨在方便大家快速的实现、比较、以及分享最新的深度文本匹配模型。 🔥 News

Neural Text Matching Community 3.7k Jan 02, 2023
Translate U is capable of translating the text present in an image from one language to the other.

Translate U is capable of translating the text present in an image from one language to the other. The app uses OCR and Google translate to identify and translate across 80+ languages.

Neelanjan Manna 1 Dec 22, 2021
This repository contains the code, models and datasets discussed in our paper "Few-Shot Question Answering by Pretraining Span Selection"

Splinter This repository contains the code, models and datasets discussed in our paper "Few-Shot Question Answering by Pretraining Span Selection", to

Ori Ram 88 Dec 31, 2022
What are the best Systems? New Perspectives on NLP Benchmarking

What are the best Systems? New Perspectives on NLP Benchmarking In Machine Learning, a benchmark refers to an ensemble of datasets associated with one

Pierre Colombo 12 Nov 03, 2022
📝An easy-to-use package to restore punctuation of the text.

✏️ rpunct - Restore Punctuation This repo contains code for Punctuation restoration. This package is intended for direct use as a punctuation restorat

Daulet Nurmanbetov 72 Dec 30, 2022
This is a modification of the OpenAI-CLIP repository of moein-shariatnia

This is a modification of the OpenAI-CLIP repository of moein-shariatnia

Sangwon Beak 2 Mar 04, 2022
This converter will create the exact measure for your cappuccino recipe from the grandiose Rafaella Ballerini!

About CappuccinoJs This converter will create the exact measure for your cappuccino recipe from the grandiose Rafaella Ballerini! Este conversor criar

Arthur Ottoni Ribeiro 48 Nov 15, 2022