Accepted Proceedings to ICRA 2023
Our target tasks are deep optical flow estimation and object detection in thermal images.
Disclaimer
-The same model was used for both synthetic and real RGB to TIR image translation
-The model was trained on identical datasets (sRGB=GTA, TIR=STheReO)
model trained on synthetic RGB image was adapted to translate real RGB image to TIR image.
Download Repo
$ git clone https://github.com/rpmsnu/sRGB-TIR.git
Docker support
To make things alot easier for environmental setup, I have uploaded my docker image on Dockerhub,
please use the following command to get the docker
$docker pull donkeymouse/donkeymouse:icra
*If there persists any problems, please file an issue!
Inference
$ python3 inference_batch.py --input_folder {input dir to your RGB images} --output_folder {output dir to store your translated images} --checkpoint {weight_file address} --a2b 0 --seed {your choice} --num_style {number of tir styles to sample} --synchronized --output_only
For example, to translate RGB images stored under a folder called "input", and say you want to sample 5 styles, run the following command:
$python3 inference_batch.py --input_folder ./input --output_folder ./output --checkpoint ./translation_weights.pt --a2b 0 --seed 1234 --num_style 5 --synchronized --output_only --config configs/tir2rgb_folder.yaml
Please download them from here: {link to google drive}
*If the link doesn't work, please file an issue!
Edge-guided multi-domain RGB2TIR translation architecture
Network Architecture
Model codes will be released after the review process has been cleared.
Training details
Please consider citing the paper as:
@ARTICLE{lee-2023-edgemultiRGB2TIR,
author={Lee, Dong-Guw and Kim, Ayoung},
conference={IEEE International Conference on Robotics and Automation},
title={Edge-guided Multi-domain RGB-to-TIR image Translation for Training Vision Tasks with Challenging Labels},
year={2023},
status={underreview}
Also, a lot of the code has been built on top of MUNIT (ECCV2018), so please go cite their paper as well.
If you have any questions, contact here please
donkeymouse@snu.ac.kr