AIM 2024 Challenge on Video Saliency Prediction: Methods and Results
Abstract
This paper reviews the Challenge on Video Saliency Prediction at AIM 2024. The goal of the participants was to develop a method for predicting accurate saliency maps for the provided set of video sequences. Saliency maps are widely exploited in various applications, including video compression, quality assessment, visual perception studies, the advertising industry, etc. For this competition, a previously unused large-scale audio-visual mouse saliency ( AViMoS ) dataset of 1500 videos with more than 70 observers per video was collected using crowdsourced mouse tracking. The dataset collection methodology has been validated using conventional eye-tracking data and has shown high consistency. Over 30 teams registered in the challenge, and there are 7 teams that submitted the results in the final phase. The final phase solutions were tested and ranked by commonly used quality metrics on a private test subset. The results of this evaluation and the descriptions of the solutions are presented in this report. All data, including the private test subset, is made publicly available on the challenge homepage— https://challenges.videoprocessing.ai/challenges/video-saliency-prediction.html .
Cite
Text
Moskalenko et al. "AIM 2024 Challenge on Video Saliency Prediction: Methods and Results." European Conference on Computer Vision Workshops, 2024. doi:10.1007/978-3-031-91856-8_11Markdown
[Moskalenko et al. "AIM 2024 Challenge on Video Saliency Prediction: Methods and Results." European Conference on Computer Vision Workshops, 2024.](https://mlanthology.org/eccvw/2024/moskalenko2024eccvw-aim/) doi:10.1007/978-3-031-91856-8_11BibTeX
@inproceedings{moskalenko2024eccvw-aim,
title = {{AIM 2024 Challenge on Video Saliency Prediction: Methods and Results}},
author = {Moskalenko, Andrey and Bryncev, Alexey and Vatolin, Dmitry S. and Timofte, Radu and Zhan, Gen and Yang, Li and Tang, Yunlong and Liao, Yiting and Lin, Jiongzhi and Huang, Baitao and Moradi, Morteza and Moradi, Mohammad and Rundo, Francesco and Spampinato, Concetto and Borji, Ali and Palazzo, Simone and Zhu, Yuxin and Sun, Yinan and Duan, Huiyu and Cao, Yuqin and Jia, Ziheng and Hu, Qiang and Min, Xiongkuo and Zhai, Guangtao and Fang, Hao and Cong, Runmin and Lu, Xiankai and Zhou, Xiaofei and Zhang, Wei and Zhao, Chunyu and Mu, Wentao and Deng, Tao and Tavakoli, Hamed R.},
booktitle = {European Conference on Computer Vision Workshops},
year = {2024},
pages = {178-194},
doi = {10.1007/978-3-031-91856-8_11},
url = {https://mlanthology.org/eccvw/2024/moskalenko2024eccvw-aim/}
}