Official implementation of the paper 'High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network' in CVPR 2021

Related tags

Deep LearningLPTN
Overview

LPTN

Paper | Supplementary Material | Poster

High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network
Jie Liang*, Hui Zeng*, and Lei Zhang.
In CVPR 2021.

Abstract

Existing image-to-image translation (I2IT) methods are either constrained to low-resolution images or long inference time due to their heavy computational burden on the convolution of high-resolution feature maps. In this paper, we focus on speeding-up the high-resolution photorealistic I2IT tasks based on closed-form Laplacian pyramid decomposition and reconstruction. Specifically, we reveal that the attribute transformations, such as illumination and color manipulation, relate more to the low-frequency component, while the content details can be adaptively refined on high-frequency components. We consequently propose a Laplacian Pyramid Translation Network (LPTN) to simultaneously perform these two tasks, where we design a lightweight network for translating the low-frequency component with reduced resolution and a progressive masking strategy to efficiently refine the high-frequency ones. Our model avoids most of the heavy computation consumed by processing high-resolution feature maps and faithfully preserves the image details. Extensive experimental results on various tasks demonstrate that the proposed method can translate 4K images in real-time using one normal GPU while achieving comparable transformation performance against existing methods.

Overall pipeline of the LPTN:

pipeline

For more details, please refer to our paper.

Getting started

  • Clone this repo.
git clone https://github.com/csjliang/LPTN
cd LPTN
  • Install dependencies. (Python 3 + NVIDIA GPU + CUDA. Recommend to use Anaconda)
pip install -r requirement.txt
  • Download dataset (FiveK in 480p) and create lmdb (to accelerate training).
PYTHONPATH="./:${PYTHONPATH}" python scripts/data_preparation/download_datasets.py
PYTHONPATH="./:${PYTHONPATH}" python scripts/data_preparation/create_lmdb.py

Training

First, check and adapt the yml file options/train/LPTN/train_FiveK.yml, then

  • Single GPU:
PYTHONPATH="./:${PYTHONPATH}" CUDA_VISIBLE_DEVICES=0 python codes/train.py -opt options/train/LPTN/train_FiveK.yml
  • Distributed Training:
PYTHONPATH="./:${PYTHONPATH}" CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node=4 --master_port=4321 codes/train.py -opt options/train/LPTN/train_FiveK.yml --launcher pytorch

Training files (logs, models, training states and visualizations) will be saved in the directory ./experiments/{name}

Evaluation

First, check and adapt the yml file options/test/LPTN/test_FiveK.yml and options/test/LPTN/test_speed_FiveK.yml, then

  • Calculate metrics and save visual results:
PYTHONPATH="./:${PYTHONPATH}" CUDA_VISIBLE_DEVICES=0 python codes/test.py -opt options/test/LPTN/test_FiveK.yml
  • Test inference speed:
PYTHONPATH="./:${PYTHONPATH}" CUDA_VISIBLE_DEVICES=0 python codes/test_speed.py -opt options/test/LPTN/test_speed_FiveK.yml

Evaluating files (logs and visualizations) will be saved in the directory ./results/{name}

Use Pretrained Models

  • Download the pretrained model from GoogleDrive and move it to the directory experiments/pretrained_models:

  • Specify the path: pretrain_network_g in test_FiveK.yml and run evaluation.

Notes

  • We have optimized the training process and improved the performance (get 22.9db on FiveK at 480p)

  • We will release the datasets of day2night and sum2win later.

Citation

If you use this dataset or code for your research, please cite our paper.

@inproceedings{jie2021LPTN,
  title={High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network},
  author={Liang, Jie and Zeng, Hui and Zhang, Lei},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  year={2021}
}

Acknowledgement

We borrowed the training and validating framework from the excellent BasicSR project.

Contact

Should you have any questions, please contact me via [email protected].

Invertible conditional GANs for image editing

Invertible Conditional GANs This is the implementation of the IcGAN model proposed in our paper: Invertible Conditional GANs for image editing. Novemb

Guim 278 Dec 12, 2022
Material del curso IIC2233 Programación Avanzada 📚

Contenidos Los contenidos se organizan según la semana del semestre en que nos encontremos, y según la semana que se destina para su estudio. Los cont

IIC2233 @ UC 72 Dec 23, 2022
CCPD: a diverse and well-annotated dataset for license plate detection and recognition

CCPD (Chinese City Parking Dataset, ECCV) UPdate on 10/03/2019. CCPD Dataset is now updated. We are confident that images in subsets of CCPD is much m

detectRecog 1.8k Dec 30, 2022
Code needed to reproduce the examples found in "The Temporal Robustness of Stochastic Signals"

The Temporal Robustness of Stochastic Signals Code needed to reproduce the examples found in "The Temporal Robustness of Stochastic Signals" Case stud

0 Oct 28, 2021
An Abstract Cyber Security Simulation and Markov Game for OpenAI Gym

gym-idsgame An Abstract Cyber Security Simulation and Markov Game for OpenAI Gym gym-idsgame is a reinforcement learning environment for simulating at

Kim Hammar 29 Dec 03, 2022
基于Paddlepaddle复现yolov5,支持PaddleDetection接口

PaddleDetection yolov5 https://github.com/Sharpiless/PaddleDetection-Yolov5 简介 PaddleDetection飞桨目标检测开发套件,旨在帮助开发者更快更好地完成检测模型的组建、训练、优化及部署等全开发流程。 PaddleD

36 Jan 07, 2023
Mask-invariant Face Recognition through Template-level Knowledge Distillation

Mask-invariant Face Recognition through Template-level Knowledge Distillation This is the official repository of "Mask-invariant Face Recognition thro

Fadi Boutros 35 Dec 06, 2022
Analysis code and Latex source of the manuscript describing the conditional permutation test of confounding bias in predictive modelling.

Git repositoty of the manuscript entitled Statistical quantification of confounding bias in predictive modelling by Tamas Spisak The manuscript descri

PNI - Predictive Neuroimaging Lab, University Hospital Essen, Germany 0 Nov 22, 2021
Learning to Reach Goals via Iterated Supervised Learning

Vanilla GCSL This repository contains a vanilla implementation of "Learning to Reach Goals via Iterated Supervised Learning" proposed by Dibya Gosh et

Christoph Heindl 4 Aug 10, 2022
Overview of architecture and implementation of TEDS-Net, as described in MICCAI 2021: "TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee TopologyPreservation in Segmentations"

TEDS-Net Overview of architecture and implementation of TEDS-Net, as described in MICCAI 2021: "TEDS-Net: Enforcing Diffeomorphisms in Spatial Transfo

Madeleine K Wyburd 14 Jan 04, 2023
A deep learning model for style-specific music generation.

DeepJ: A model for style-specific music generation https://arxiv.org/abs/1801.00887 Abstract Recent advances in deep neural networks have enabled algo

Henry Mao 704 Nov 23, 2022
A Pytorch loader for MVTecAD dataset.

MVTecAD A Pytorch loader for MVTecAD dataset. It strictly follows the code style of common Pytorch datasets, such as torchvision.datasets.CIFAR10. The

Jiyuan 1 Dec 27, 2021
The official implementation for ACL 2021 "Challenges in Information Seeking QA: Unanswerable Questions and Paragraph Retrieval".

Code for "Challenges in Information Seeking QA: Unanswerable Questions and Paragraph Retrieval" (ACL 2021, Long) This is the repository for baseline m

Akari Asai 25 Oct 30, 2022
Picasso: A CUDA-based Library for Deep Learning over 3D Meshes

The Picasso Library is intended for complex real-world applications with large-scale surfaces, while it also performs impressively on the small-scale applications over synthetic shape manifolds. We h

97 Dec 01, 2022
STRIVE: Scene Text Replacement In Videos

STRIVE: Scene Text Replacement In Videos Dataset Types: RoboText SynthText RealWorld videos RoboText : Videos of texts collected using navigation robo

15 Jul 11, 2022
Code release for "MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound"

merlot_reserve Code release for "MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound" MERLOT Reserve (in submission) is a mo

Rowan Zellers 92 Dec 11, 2022
AI grand challenge 2020 Repo (Speech Recognition Track)

KorBERT를 활용한 한국어 텍스트 기반 위협 상황인지(2020 인공지능 그랜드 챌린지) 본 프로젝트는 ETRI에서 제공된 한국어 korBERT 모델을 활용하여 폭력 기반 한국어 텍스트를 분류하는 다양한 분류 모델들을 제공합니다. 본 개발자들이 참여한 2020 인공지

Young-Seok Choi 23 Jan 25, 2022
Code release for the paper “Worldsheet Wrapping the World in a 3D Sheet for View Synthesis from a Single Image”, ICCV 2021.

Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image This repository contains the code for the following paper: R. Hu,

Meta Research 37 Jan 04, 2023
Using VapourSynth with super resolution models and speeding them up with TensorRT.

VSGAN-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Using NVIDIA/Torch-TensorRT combined wi

111 Jan 05, 2023
Code for pre-training CharacterBERT models (as well as BERT models).

Pre-training CharacterBERT (and BERT) This is a repository for pre-training BERT and CharacterBERT. DISCLAIMER: The code was largely adapted from an o

Hicham EL BOUKKOURI 31 Dec 05, 2022