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Code for paper "Saliency-aware Stereoscopic Video Retargeting"

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SVR

Code for paper "Saliency-aware Stereoscopic Video Retargeting"

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Training

First install the requirements:

pip3 install requirements

Download the datasets

First fownload the KITTI stereo video 2015 and 2012 datasets from the following link:

https://www.cvlibs.net/datasets/kitti/eval_stereo.php

Unzip and put the datasets in the "datasets/" directory.

Download the weights of CoSD [1]

Download the weights of the saliency detection method from the following like:

https://github.com/suyukun666/UFO

Put them in the "models/" directory.

For calculating the perceptual loss [2], clone the following repository and put it in the "PerceptualSimilarity/" directory:

https://github.com/SteffenCzolbe/PerceptualSimilarity

Start training

Run the following command to start the training:

sudo python3 main.py --train_or_test train

The trained model will be saved in the "models/" directory.

Testing

Download the pre-trained model from th following link as put it in "models/" directory:

https://drive.google.com/file/d/11mlx1PRh-oFzOTLABAkySk7_DGLvEmyw/view?usp=share_link

Run the following command to start testing:

sudo python3 main.py --train_or_test test

References

[1] Yukun Su, Jingliang Deng, Ruizhou Sun, Guosheng Lin, and Qingyao Wu. A unified transformer framework for group-based segmentation: Co-segmentation, co-saliency detection and video salient object detection. arXiv preprint arXiv:2203.04708, 2022. 3

[2] Czolbe, Steffen, et al. "A loss function for generative neural networks based on watson’s perceptual model." Advances in Neural Information Processing Systems 33 (2020): 2051-2061.

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