SelfSVD (ECCV 2024, Oral)

PyTorch implementation of Self-Supervised Video Desmoking for Laparoscopic Surgery

News

• 🔥 Laparoscopic surgery video desmoking (LSVD) dataset is now available.
• 🔥 SelfSVD codes are now available.

In this work, we suggest utilizing the internal characteristics of real-world surgery videos for effective self-supervised video desmoking, and propose a SelfSVD solution.

1. Abstract

Due to the difficulty of collecting real paired data, most existing desmoking methods train the models by synthesizing smoke, generalizing poorly to real surgical scenarios. Although a few works have explored single-image real-world desmoking in unpaired learning manners, they still encounter challenges in handling dense smoke. In this work, we address these issues together by introducing the self-supervised surgery video desmoking (SelfSVD). On the one hand, we observe that the frame captured before the activation of high-energy devices is generally clear (named pre-smoke frame, PS frame), thus it can serve as supervision for other smoky frames, making real-world self-supervised video desmoking practically feasible. On the other hand, in order to enhance the desmoking performance, we further feed the valuable information from PS frame into models, where a masking strategy and a regularization term are presented to avoid trivial solutions. In addition, we construct a real surgery video dataset for desmoking, which covers a variety of smoky scenes. Extensive experiments on the dataset show that our SelfSVD can remove smoke more effectively and efficiently while recovering more photo-realistic details than the state-of-the-art methods.

2. Prerequisites and Datasets

3.1 Prerequisites

• Python 3.10.9, PyTorch 1.12.1, cuda-11.3
• mmcv 1.7.1, cupy-cuda113, opencv, numpy, Pillow, timm, tqdm, scikit-image

3.2 LSVD Dataset

Please download the data from Baidu Netdisk (Chinese: 百度网盘).

• Please Fill Dataset Request Form via Baidu Cloud, and send it to hirenlongwu@gmail.com with this form ( Non-institutional emails (e.g. gmail.com) are not allowed. Please provide your institutional email address.).
• LSVD dataset link: https://pan.baidu.com/s/1nsK-Qvtl-m8haaO7V8-VlA?pwd=0a4w

3.3 Pretrained models

• The pretrained models link: https://pan.baidu.com/s/1N-qsyW14310dZyrFdYvl_Q?pwd=i3w2

3.4. Quick Start

• Train SelfSVD, run bash ./train_selfsvd.sh
• Test SelfSVD, run bash ./test_selfsvd.sh
• Train SelfSVDstar, run bash ./train_selfsvdstar.sh
• Test SelfSVDstar, run bash ./test_selfsvdstar.sh

3.5 Custom Dataset

• You can obtain the mask with python ./script_mask_generate.py/script_mask_generate.py

4. Desmoking Results on LSVD Dataset

5. Desmoking Results on real surgery videos

Please wait a few seconds for loading videos.

Input Smoky Video	Output Video

## Acknowledgement

Special thanks to the following awesome projects!

• MMEditing
• MAP-Net

Citation

If you make use of our work, please cite our paper.

@article{selfsvd,
  title={Self-Supervised Video Desmoking for Laparoscopic Surgery},
  author={Wu, Renlong and Zhang, Zhilu and Zhang, Shuohao and Gou, Longfei and Chen, Haobin and Zhang, Lei and Chen, Hao and Zuo, Wangmeng},
  journal={ECCV},
  year={2024}
}