URVIS 2026 is the first challenge on adverse-to-extreme panoptic segmentation, drawing 17 participants and 47 submissions while introducing weighted Panoptic Quality as the ranking metric on the MUSES dataset.
Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform.Patterns, 3(7):100543, 2022
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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.
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Adverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark
URVIS 2026 is the first challenge on adverse-to-extreme panoptic segmentation, drawing 17 participants and 47 submissions while introducing weighted Panoptic Quality as the ranking metric on the MUSES dataset.
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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.