We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

Related tags

Deep Learningcomputer-visiondeep-learningrenderingcomputer-graphicsvoxelpoint-cloudpytorchmeshganneural-networksshapenet3d-reconstructionloss-functionsshapenet-datasetcub-datasetpascal3dpose-predic
Overview

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering

Papers with code | Paper

Nikola Zubić   Pietro Lio  

University of Novi Sad   University of Cambridge

AIAI 2021

Citation

Besides AIAI 2021, our paper is in a Springer's book entitled "Artificial Intelligence Applications and Innovations": link

Please, cite our paper if you find this code useful for your research.

@article{zubic2021effective,
  title={An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering},
  author={Zubi{\'c}, Nikola and Li{\`o}, Pietro},
  journal={arXiv preprint arXiv:2103.03390},
  year={2021}
}

Prerequisites

  • Download code:
    Git clone the code with the following command:

    git clone https://github.com/NikolaZubic/2dimageto3dmodel.git

  • Open the project with Conda Environment (Python 3.7)

  • Install packages:

    conda install pytorch torchvision torchaudio cudatoolkit=11.0 -c pytorch

    Then git clone Kaolin library in the root (2dimageto3dmodel) folder with the following commit and run the following commands:

    cd kaolin
python setup.py install
pip install --no-dependencies nuscenes-devkit opencv-python-headless scikit-learn joblib pyquaternion cachetools
pip install packaging

Run the program

Run the following commands from the root/code/ (2dimageto3dmodel/code/) directory:

python main.py --dataset cub --batch_size 16 --weights pretrained_weights_cub --save_results

for the CUB Birds Dataset. 

python main.py --dataset p3d --batch_size 16 --weights pretrained_weights_p3d --save_results

for the Pascal 3D+ Dataset.

The results will be saved at 2dimageto3dmodel/code/results/ path.

Continue training

To continue the training process:
Run the following commands (without --save_results) from the root/code/ (2dimageto3dmodel/code/) directory:

python main.py --dataset cub --batch_size 16 --weights pretrained_weights_cub

for the CUB Birds Dataset. 

python main.py --dataset p3d --batch_size 16 --weights pretrained_weights_p3d

for the Pascal 3D+ Dataset.

License

MIT

Acknowledgment

This idea has been built based on the architecture of Insafutdinov & Dosovitskiy.
Poisson Surface Reconstruction was used for Point Cloud to 3D Mesh transformation.
The GAN architecture (used for texture mapping) is a mixture of Xian's TextureGAN and Li's GAN.

Comments
  • Where is cmr_data?

    Where is cmr_data?

    Keep running into this issue from cmr_data.p3d import P3dDataset and from cmr_data.p3d import CUBDataset

    but you do not have these files in your repo. I tried using cub_200_2011_dataset.py but it does not take in the same number of arguments as the CUBDataset class used in run_reconstruction.py.

    opened by achhabria7 6
  • ModuleNotFoundError: No module named 'kaolin.graphics'

    ModuleNotFoundError: No module named 'kaolin.graphics'

    Pascal 3D+ dataset with 4722 images is successfully loaded.

    Traceback (most recent call last): File "main.py", line 149, in <module> from rendering.renderer import Renderer File "/home/ujjawal/my_work/object_recon/2d3d/code/rendering/renderer.py", line 1, in <module> from kaolin.graphics.dib_renderer.rasterizer import linear_rasterizer ModuleNotFoundError: No module named kaolin.graphics

    I also downloaded the graphics folder from here https://github.com/NVIDIAGameWorks/kaolin/tree/e7e513173bd4159ae45be6b3e156a3ad156a3eb9 and tried to place in the graphics folder in the kaolin folder locally and here is the error Traceback (most recent call last): File "main.py", line 149, in <module> from rendering.renderer import Renderer File "/home/ujjawal/my_work/object_recon/2d3d/code/rendering/renderer.py", line 1, in <module> from kaolin.graphics.dib_renderer.rasterizer import linear_rasterizer File "/usr/local/lib/python3.6/dist-packages/kaolin-0.9.0-py3.6-linux-x86_64.egg/kaolin/graphics/__init__.py", line 2, in <module> File "/usr/local/lib/python3.6/dist-packages/kaolin-0.9.0-py3.6-linux-x86_64.egg/kaolin/graphics/nmr/__init__.py", line 1, in <module> File "/usr/local/lib/python3.6/dist-packages/kaolin-0.9.0-py3.6-linux-x86_64.egg/kaolin/graphics/nmr/rasterizer.py", line 30, in <module> ImportError: cannot import name rasterize_cuda

    opened by ujjawalcse 6
  • No module named 'models.reconstruction'

    No module named 'models.reconstruction'

    Dear NikolaZubic :
    Thanks for you updated the code recently. Did you put the reconstruction.py in the models folder？When I run “python run_reconstruction.py --name pretrained_reconstruction_cub --dataset cub --batch_size 10 --generate_pseudogt” it display
    No module named 'models.reconstruction.

    opened by lw0210 2
  • inference with single RGB pictures

    inference with single RGB pictures

    Hi, I am interested with your work, it is wonderful, and I want to use my own picture to test the model, could you provided the pretrained model and inference scripts.

    opened by 523997931 2
  • can't find the pseudogt_512*512\.npz file

    can't find the pseudogt_512*512\.npz file

    Dear NikolaZubic: I want to quote your paper, but I can't find the pseudogt_512512.npz file and can't reproduce it. Can you give me the pseudogt_512512.npz file and help me reproduce it? Thanks

    opened by Yangfuha 1
  • ValueError: Training a model requires the pseudo-ground-truth to be setup beforehand.

    ValueError: Training a model requires the pseudo-ground-truth to be setup beforehand.

    I recently read your paper and was very interested in it . I want to reproduce the code of this paper. When I followed your instructions, I found it difficult for me to run the commands（python main.py --dataset cub --batch_size 16 --weights pretrained_weights_cub and python main.py --dataset p3d --batch_size 16 --weights pretrained_weights_p3d.）.And the program displayed a value error that training a model requires the pseudo-ground-truth to be setup beforehand. And I don’t know how to solve the problem, so I turn to you for help.I'm sorry to bother you, but I'really eager to solve the problem. I hope to get your reply.Thank you!

    opened by lw0210 1
  • Added step: switch to the correct correct Kaolin branch

    Added step: switch to the correct correct Kaolin branch

    This step will help others to avoid the "ModuleNotFoundError: No module named kaolin.graphics" error.

    Fix to issue: https://github.com/NikolaZubic/2dimageto3dmodel/issues/2

    opened by ricklentz 1
  • Shapenet V2 not training

    Shapenet V2 not training

    Great work guys. I was able to run the code on CUB dataset. But when I tried to run training_test_shape_net.py on Shape Net v2 chair class I'm getting errors because of missing files, unmatched file names, etc.

    So it would be helpful if you provide Shapenet Dataset Folder structure and files(images, masks) description or a sample folder and clear instructions for training the model shapenet dataset. And also if possible give pre-trained weights for the Shape net dataset models

    Thank you

    opened by girishdhegde 0
  • Pretrained model

    Pretrained model

    Hi, I find it hard to understand how to train the model on ShapeNet. It would be very helpful if you can provide a pretrained model on ShapeNet planes (I need it to test the performance in my project). If the pretrained models are not available, it would also be helpful to introduce me of how to train the model on ShapeNet.

    opened by YYYYYHC 0
  • How can I train on the boat set of the Pascal 3D+ dataset

    How can I train on the boat set of the Pascal 3D+ dataset

    I find the data of trainning such as "python run_reconstruction.py --name pretrained_reconstruction_p3d --dataset p3d --optimize_z0 --batch_size 50 --tensorboard" using the data of car.mat in sfm and data folder.Even if I rename the .mat to boat.mat and using the boat imageNet in Pascal 3D+ dataset,I find the shape of the result is more like a car not a boat.So I am wondering how to train the boat set.

    opened by lisentao 0
  • Custom Dataset

    Custom Dataset

    Hi!

    Love the work you guys have done. I am currently conducting a research. Could you please tell me how I would train on a custom dataset and how I would infer an image or create a 3d model out an image with pretrained weights that you have provided?

    opened by mahnoor-fatima-saad 0
  • How do I make my own dataset？

    How do I make my own dataset？

    Dear NikolaZubic： I want to use my own data set to replace the cub or P3D data set for training. Do you have any attention or requirements for images when making data sets?

    opened by lw0210 0
Releases(metadata)
Owner
Nikola Zubić
Interested in Artificial intelligence, Visual Computing and Cognitive science. For future AI projects: @reinai
Nikola Zubić
GitHub Repository
The devkit of the nuPlan dataset.

The devkit of the nuPlan dataset.

Motional 264 Jan 03, 2023
Playing around with FastAPI and streamlit to create a YoloV5 object detector

FastAPI-Streamlit-based-YoloV5-detector Playing around with FastAPI and streamlit to create a YoloV5 object detector It turns out that a User Interfac

2 Jan 20, 2022
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19

2s-AGCN Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19 Note PyTorch version should be 0.3! For PyTor

LShi 547 Dec 26, 2022
Vector AI — A platform for building vector based applications. Encode, query and analyse data using vectors.

Vector AI is a framework designed to make the process of building production grade vector based applications as quickly and easily as possible. Create

Vector AI 267 Dec 23, 2022
OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:

Nouroz Rahman 410 Jan 05, 2023
My usage of Real-ESRGAN to upscale anime, some test and results in the test_img folder

anime upscaler My usage of Real-ESRGAN to upscale anime, I hope to use this on a proper GPU cuz doing this on CPU is completely shit 😂 , I even tried

Shangar Muhunthan 29 Jan 07, 2023
Pytorch code for "Text-Independent Speaker Verification Using 3D Convolutional Neural Networks".

:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification

Amirsina Torfi 114 Dec 18, 2022
A curated list of awesome Model-Based RL resources

Awesome Model-Based Reinforcement Learning This is a collection of research papers for model-based reinforcement learning (mbrl). And the repository w

OpenDILab 427 Jan 03, 2023
VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning

    VarCLR: Variable Representation Pre-training via Contrastive Learning New: Paper accepted by ICSE 2022. Preprint at arXiv! This repository contain

squaresLab 32 Oct 24, 2022
This repo is developed for Strong Baseline For Vehicle Re-Identification in Track 2 Ai-City-2021 Challenges

A STRONG BASELINE FOR VEHICLE RE-IDENTIFICATION This paper is accepted to the IEEE Conference on Computer Vision and Pattern Recognition Workshop(CVPR

Cybercore Co. Ltd 78 Dec 29, 2022
BuildingNet: Learning to Label 3D Buildings

BuildingNet This is the implementation of the BuildingNet architecture described in this paper: Paper: BuildingNet: Learning to Label 3D Buildings Arx

16 Nov 07, 2022
Adversarial Learning for Modeling Human Motion

Adversarial Learning for Modeling Human Motion This repository contains the open source code which reproduces the results for the paper: Adversarial l

wangqi 6 Jun 15, 2021
Basit bir burç modülü.

Bu modulu burclar hakkinda gundelik bir sekilde bilgi alin diye yaptim ve sizler icin kullanima sunuyorum. Modulun kullanimi asiri basit: Ornek Kullan

Special 17 Jun 08, 2022
FastyAPI is a Stack boilerplate optimised for heavy loads.

FastyAPI A FastAPI based Stack boilerplate for heavy loads. Explore the docs » View Demo · Report Bug · Request Feature Table of Contents About The Pr

Ali Chaayb 47 Dec 27, 2022
PolyGlot, a fuzzing framework for language processors

PolyGlot, a fuzzing framework for language processors Build We tested PolyGlot on Ubuntu 18.04. Get the source code: git clone https://github.com/s3te

Software Systems Security Team at Penn State University 79 Dec 27, 2022
Code for Ditto: Building Digital Twins of Articulated Objects from Interaction

Ditto: Building Digital Twins of Articulated Objects from Interaction Zhenyu Jiang, Cheng-Chun Hsu, Yuke Zhu CVPR 2022, Oral Project | arxiv News 2022

UT Robot Perception and Learning Lab 78 Dec 22, 2022
HandFoldingNet ✌️ : A 3D Hand Pose Estimation Network Using Multiscale-Feature Guided Folding of a 2D Hand Skeleton

HandFoldingNet ✌️ : A 3D Hand Pose Estimation Network Using Multiscale-Feature Guided Folding of a 2D Hand Skeleton Wencan Cheng, Jae Hyun Park, Jong

cwc1260 23 Oct 21, 2022
Group-Free 3D Object Detection via Transformers

Group-Free 3D Object Detection via Transformers By Ze Liu, Zheng Zhang, Yue Cao, Han Hu, Xin Tong. This repo is the official implementation of "Group-

Ze Liu 213 Dec 07, 2022
This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer

OODformer: Out-Of-Distribution Detection Transformer This repo is the official the implementation of the OODformer: Out-Of-Distribution Detection Tran

34 Dec 02, 2022
Unsupervised Image-to-Image Translation

UNIT: UNsupervised Image-to-image Translation Networks Imaginaire Repository We have a reimplementation of the UNIT method that is more performant. It

Ming-Yu Liu 劉洺堉 1.9k Dec 26, 2022