The official repository for BaMBNet

Related tags

Deep LearningBaMBNet
Overview

BaMBNet-Pytorch

Paper: https://arxiv.org/abs/2105.14766 (arXiv)

The code is for the work:

@article{liang2021BaMBNet,
  title={BaMBNet: A Blur-aware Multi-branch Network for Defocus Deblurring},
  author={Pengwei Liang, Junjun Jiang, Xianming Liu, and Jiayi Ma},
  journal={submitted to IEEE Transactions on Computational Imaging},
  volume={},
  number={},
  pages={},
  year={2021},
}

Requirements

pytorch == 1.7.1
kornia == 0.4.1
opencv == 4.4.0

Dataset

Please refer to the official repo at Defocus deblurring using dual-pixel data.

Train

  • Step 1: train COC network to estimate the blur amounts of DP data.

    python blur_train.py -opt option/train/COC_Dataset_Train.yaml
  • Step 2: prepare the COC maps for deblurring training.

    python blur_test.py -opt option/test/COC_Dataset_Test.yaml
  • Step 3: train the deblurred network.

    python train.py -opt option/train/Deblur_Dataset_Trained.yaml

Test

python test.py -opt option/test/Deblur_Dataset_Test.yaml

License

This project is under the CC-BY-NC 4.0 license. See LICENSE for details.

Owner
Junjun Jiang
He is a Professor at HIT, Harbin, China.
Junjun Jiang
Script for getting information in discord

User-info.py Script for getting information in https://discord.com/ Instalação: apt-get update -y apt-get upgrade -y apt-get install git pkg install

Moleey 1 Dec 18, 2021
Code for the paper "Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness"

DU-VAE This is the pytorch implementation of the paper "Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness" Acknowledgement

Dazhong Shen 4 Oct 19, 2022
[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision

TorchSemiSeg [CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision by Xiaokang Chen1, Yuhui Yuan2, Gang Zeng1, Jingdong Wang

Chen XiaoKang 387 Jan 08, 2023
This is a collection of our NAS and Vision Transformer work.

AutoML - Neural Architecture Search This is a collection of our AutoML-NAS work iRPE (NEW): Rethinking and Improving Relative Position Encoding for Vi

Microsoft 828 Dec 28, 2022
Kaggle-titanic - A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.

Kaggle-titanic This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this reposito

Andrew Conti 800 Dec 15, 2022
Re-TACRED: Addressing Shortcomings of the TACRED Dataset

Re-TACRED Re-TACRED: Addressing Shortcomings of the TACRED Dataset

George Stoica 40 Dec 10, 2022
Ray tracing of a Schwarzschild black hole written entirely in TensorFlow.

TensorGeodesic Ray tracing of a Schwarzschild black hole written entirely in TensorFlow. Dependencies: Python 3 TensorFlow 2.x numpy matplotlib About

5 Jan 15, 2022
Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron

Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron

Roxbili 5 Nov 19, 2022
Must-read Papers on Physics-Informed Neural Networks.

PINNpapers Contributed by IDRL lab. Introduction Physics-Informed Neural Network (PINN) has achieved great success in scientific computing since 2017.

IDRL 330 Jan 07, 2023
Implementation of association rules mining algorithms (Apriori|FPGrowth) using python.

Association Rules Mining Using Python Implementation of association rules mining algorithms (Apriori|FPGrowth) using python. As a part of hw1 code in

Pre 2 Nov 10, 2021
Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification

Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification Usage The required packages are lis

0 Feb 07, 2022
Pytorch implementation of "Neural Wireframe Renderer: Learning Wireframe to Image Translations"

Neural Wireframe Renderer: Learning Wireframe to Image Translations Pytorch implementation of ideas from the paper Neural Wireframe Renderer: Learning

Yuan Xue 7 Nov 14, 2022
Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch

CoCa - Pytorch Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch. They were able to elegantly fit in contras

Phil Wang 565 Dec 30, 2022
unet-family: Ultimate version

unet-family: Ultimate version 基于之前my-unet代码,我整理出来了这一份终极版本unet-family,方便其他人阅读。 相比于之前的my-unet代码,代码分类更加规范,有条理 对于clone下来的代码不需要修改各种复杂繁琐的路径问题,直接就可以运行。 并且代码有

2 Sep 19, 2022
Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression

Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx

Arsenii Senya Ashukha 80 Sep 17, 2022
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution This is the official implementation code of the paper "CondLaneNe

Alibaba Cloud 311 Dec 30, 2022
Torch implementation of SegNet and deconvolutional network

Torch implementation of SegNet and deconvolutional network

Fedor Chervinskii 5 Jul 17, 2020
[ICLR'19] Trellis Networks for Sequence Modeling

TrellisNet for Sequence Modeling This repository contains the experiments done in paper Trellis Networks for Sequence Modeling by Shaojie Bai, J. Zico

CMU Locus Lab 460 Oct 13, 2022
Source code for "Pack Together: Entity and Relation Extraction with Levitated Marker"

PL-Marker Source code for Pack Together: Entity and Relation Extraction with Levitated Marker. Quick links Overview Setup Install Dependencies Data Pr

THUNLP 173 Dec 30, 2022
Official Implement of CVPR 2021 paper “Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting”

RGBT Crowd Counting Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin. "Cross-Modal Collaborative Representation Learning and a L

37 Dec 08, 2022