Explore the best methods of video saliency prediction (VSP) algorithms

Our benchmark determines the best video saliency prediction methods for recognition of the most important areas of the video using our compact yet comprehensive dataset.

Everyone is welcome to participate! Run your favorite video saliency prediction method on our dataset and send us the result to see how well it performs. Check the “Submitting” section to learn the details.

What’s new

• May 25th, 2023: Beta-version Release

Introduction

We use various objective metrics for evaluating video saliency prediction methods. Also, we calculate the average FPS (frames per second) to compare the speed of the algorithms.

To generalize the output of the models, we use the domain adaptation involving such transformations as brightness correction and blending with the Center Prior. Check the “Methodology” section to learn the details.

Scroll below for comparison charts, tables, and interactive visual comparisons of saliency model results.

Visualizations

Leaderboards

Charts

Submitting

To add your video saliency prediction method to the benchmark, follow these steps:

1. Download the input	Download the dataset
2. Apply your method	Apply your video saliency prediction method to the dataset
3. Send us the result	Send to video-saliency-prediction-benchmark@videoprocessing.ai the following information: The full and short names of the video saliency prediction method that we will specify in our benchmark. An compressed directory with saliency maps. The link must be valid within a month after receiving it. Please ensure that you permit us to download the file. By submitting this video, you agree that third parties may use it. The exact commands, options, versions of used programs, etc. Each submission must contain results of exactly one model with fixed settings. Please do not fine-tune model parameters by hand for each video segment. If you want us to verify your method, send us the executable, and we will run it ourselves. Then we will mark the FPS of your algorithm as “Verified” in charts and tables. Executable's arguments must include paths to the folder with input PNG images and the folder for output PNG images. By submitting this executable, you agree that third parties may use it.

If you have any suggestions or questions, please contact us: video-saliency-prediction-benchmark@videoprocessing.ai

Get Notifications About the Updates of This Benchmark

Do you want to be the first to discover the best new video saliency prediction algorithm? We can notify you about this benchmark’s updates: simply submit your preferred email address using the form below. We promise not to send you unrelated information.

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Further Reading

Check the “Methodology” section to learn how we prepare our dataset.

Check the “Participants” section to learn which video saliency prediction method implementations we use.