Official PyTorch Implementation of Convolutional Hough Matching Networks, CVPR 2021 (oral)

Overview

PWC
PWC
PWC

Convolutional Hough Matching Networks

This is the implementation of the paper "Convolutional Hough Matching Network" by J. Min and M. Cho. Implemented on Python 3.7 and PyTorch 1.3.1.

For more information, check out project [website] and the paper on [arXiv]

Overall architecture:

Requirements

  • Python 3.7
  • PyTorch 1.3.1
  • cuda 10.1
  • pandas
  • requests

Conda environment settings:

conda create -n chm python=3.7
conda activate chm

conda install pytorch=1.3.1 torchvision cudatoolkit=10.1 -c pytorch
conda install -c anaconda requests
conda install -c conda-forge tensorflow
pip install tensorboardX
conda install -c anaconda pandas

Training

The code provides three types of CHM kernel: position-sensitive isotropic (psi), isotropic (iso), vanilla Nd (full).

python train.py --ktype {psi, iso, full} 
                --benchmark {spair, pfpascal}

Testing

Trained models are available on [Google drive].

python test.py --ktype {psi, iso, full} 
               --benchmark {spair, pfpascal, pfwillow} 
               --load 'path_to_trained_model'

For example, to reproduce our results in Table 1, refer following scripts.

python test.py --ktype psi --benchmark spair --load 'path_to_trained_model/spr_psi.pt'
python test.py --ktype psi --benchmark spair --load 'path_to_trained_model/pas_psi.pt'
python test.py --ktype psi --benchmark pfpascal --load 'path_to_trained_model/pas_psi.pt'
python test.py --ktype psi --benchmark pfwillow --load 'path_to_trained_model/pas_psi.pt'

BibTeX

If you use this code for your research, please consider citing:

@InProceedings{min2021chm, 
    author    = {Min, Juhong and Cho, Minsu},
    title     = {Convolutional Hough Matching Networks},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2021},
    pages     = {2940-2950}
}
Owner
Juhong Min
research interest in computer vision
Juhong Min
Code for our EMNLP 2021 paper “Heterogeneous Graph Neural Networks for Keyphrase Generation”

GATER This repository contains the code for our EMNLP 2021 paper “Heterogeneous Graph Neural Networks for Keyphrase Generation”. Our implementation is

Jiacheng Ye 12 Nov 24, 2022
converts nominal survey data into a numerical value based on a dictionary lookup.

SWAP RATE Converts nominal survey data into a numerical values based on a dictionary lookup. It allows the user to switch nominal scale data from text

Jake Rhodes 1 Jan 18, 2022
Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)

Junction Tree Variational Autoencoder for Molecular Graph Generation Official implementation of our Junction Tree Variational Autoencoder https://arxi

Wengong Jin 418 Jan 07, 2023
PyTorch implementation of Asymmetric Siamese (https://arxiv.org/abs/2204.00613)

Asym-Siam: On the Importance of Asymmetry for Siamese Representation Learning This is a PyTorch implementation of the Asym-Siam paper, CVPR 2022: @inp

Meta Research 89 Dec 18, 2022
Tools for manipulating UVs in the Blender viewport.

UV Tool Suite for Blender A set of tools to make editing UVs easier in Blender. These tools can be accessed wither through the Kitfox - UV panel on th

35 Oct 29, 2022
A simple baseline for 3d human pose estimation in tensorflow. Presented at ICCV 17.

3d-pose-baseline This is the code for the paper Julieta Martinez, Rayat Hossain, Javier Romero, James J. Little. A simple yet effective baseline for 3

Julieta Martinez 1.3k Jan 03, 2023
Anomaly detection in multi-agent trajectories: Code for training, evaluation and the OpenAI highway simulation.

Anomaly Detection in Multi-Agent Trajectories for Automated Driving This is the official project page including the paper, code, simulation, baseline

12 Dec 02, 2022
SiT: Self-supervised vIsion Transformer

This repository contains the official PyTorch self-supervised pretraining, finetuning, and evaluation codes for SiT (Self-supervised image Transformer).

Sara Ahmed 275 Dec 28, 2022
🔥 Cannlytics-powered artificial intelligence 🤖

Cannlytics AI 🔥 Cannlytics-powered artificial intelligence 🤖 🏗️ Installation 🏃‍♀️ Quickstart 🧱 Development 🦾 Automation 💸 Support 🏛️ License ?

Cannlytics 3 Nov 11, 2022
Self-Supervised Learning with Kernel Dependence Maximization

Self-Supervised Learning with Kernel Dependence Maximization This is the code for SSL-HSIC, a self-supervised learning loss proposed in the paper Self

DeepMind 29 Dec 29, 2022
This repository will be a summary and outlook on all our open, medical, AI advancements.

medical by LAION This repository will be a summary and outlook on all our open, medical, AI advancements. See the medical-general channel in the medic

LAION AI 18 Dec 30, 2022
Notebooks, slides and dataset of the CorrelAid Machine Learning Winter School

CorrelAid Machine Learning Winter School Welcome to the CorrelAid ML Winter School! Task The problem we want to solve is to classify trees in Roosevel

CorrelAid 12 Nov 23, 2022
Convert weight file.pth to weight file.blob

CONVERT YOUR MODEL TO IR FORMAT INSTALLATION OpenVino Toolkit Download openvinotoolkit 2021.3 version : Link Instruction of installation : Link Pytorc

Tran Anh Tuan 3 Nov 18, 2021
Real-time pose estimation accelerated with NVIDIA TensorRT

trt_pose Want to detect hand poses? Check out the new trt_pose_hand project for real-time hand pose and gesture recognition! trt_pose is aimed at enab

NVIDIA AI IOT 803 Jan 06, 2023
ICRA 2021 - Robust Place Recognition using an Imaging Lidar

Robust Place Recognition using an Imaging Lidar A place recognition package using high-resolution imaging lidar. For best performance, a lidar equippe

Tixiao Shan 293 Dec 27, 2022
Accelerated deep learning R&D

Accelerated deep learning R&D PyTorch framework for Deep Learning research and development. It focuses on reproducibility, rapid experimentation, and

Catalyst-Team 3.1k Jan 06, 2023
Implementation of Axial attention - attending to multi-dimensional data efficiently

Axial Attention Implementation of Axial attention in Pytorch. A simple but powerful technique to attend to multi-dimensional data efficiently. It has

Phil Wang 250 Dec 25, 2022
Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space"

Sparse Steerable Convolution (SS-Conv) Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and

25 Dec 21, 2022
Large scale PTM - PPI relation extraction

Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT The silver standard

1 Feb 25, 2022
Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"

The Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more" Arxiv preprint Louay Hazami   ·   Rayhane Mama   ·   Ragavan Thurairatn

Rayhane Mama 144 Dec 23, 2022