The PhyScore challenge creates the first benchmark requiring metrics to jointly score video quality, physical realism, condition alignment, and temporal consistency while localizing physical anomalies in 1554 videos from seven generative models across text-to-2D, image-to-4D, and video-to-4D tracks.
LoViF 2026 challenge on real-world all-in-one im- age restoration: Methods and results
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The LoViF 2026 Challenge creates the SeIQA dataset and benchmark for human-oriented semantic image quality assessment, with six submitted solutions reaching state-of-the-art performance.
The LoViF 2026 challenge introduces a short-form video weather removal dataset and summarizes results from 5 valid submissions out of 37 participants.
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LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)
The PhyScore challenge creates the first benchmark requiring metrics to jointly score video quality, physical realism, condition alignment, and temporal consistency while localizing physical anomalies in 1554 videos from seven generative models across text-to-2D, image-to-4D, and video-to-4D tracks.
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LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment: Methods and Results
The LoViF 2026 Challenge creates the SeIQA dataset and benchmark for human-oriented semantic image quality assessment, with six submitted solutions reaching state-of-the-art performance.
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LoViF 2026 The First Challenge on Weather Removal in Videos
The LoViF 2026 challenge introduces a short-form video weather removal dataset and summarizes results from 5 valid submissions out of 37 participants.