mlsanityData to 7 Oct 2026

NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results

arXiv 2604.14816 ↗First posted 16 Apr 2026cs.CV cs.HC cs.MMcited by 10

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Abstract (arXiv)

This paper presents an overview of the NTIRE 2026 Challenge on Video Saliency Prediction. The goal of the challenge participants was to develop automatic saliency map prediction methods for the provided video sequences. The novel dataset of 2,000 diverse videos with an open license was prepared for this challenge. The fixations and corresponding saliency maps were collected using crowdsourced mouse tracking and contain viewing data from over 5,000 assessors. Evaluation was performed on a subset of 800 test videos using generally accepted quality metrics. The challenge attracted over 20 teams making submissions, and 7 teams passed the final phase with code review. All data used in this challenge is made publicly available - https://github.com/msu-video-group/NTIRE26_Saliency_Prediction.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 54 of its 107 references that are in the map. First posted on arXiv 16 Apr 2026.

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54 of 107 references.

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38 more
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