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Datasets/OpenS2V-Eval

OpenS2V-Eval

ImagesTextsVideosCC-BY-4.0Introduced 2025-05-26

OpenS2V-Eval introduces 180 prompts from seven major categories of S2V, which incorporate both real and synthetic test data. Furthermore, to accurately align human preferences with S2V benchmarks, we propose three automatic metrics: NexusScore, NaturalScore, GmeScore to separately quantify subject consistency, naturalness, and text relevance in generated videos. Building on this, we conduct a comprehensive evaluation of 14 representative S2V models, highlighting their strengths and weaknesses across different content.

Benchmarks

1 Image, 2*2 Stitchi/Total Score1 Image, 2*2 Stitchi/Venue1 Image, 2*2 Stitchi/Aesthetics1 Image, 2*2 Stitchi/Motion1 Image, 2*2 Stitchi/FaceSim1 Image, 2*2 Stitchi/GmeScore1 Image, 2*2 Stitchi/NexusScore1 Image, 2*2 Stitchi/NaturalScoreImage to Video Generation/Total ScoreImage to Video Generation/VenueImage to Video Generation/AestheticsImage to Video Generation/MotionImage to Video Generation/FaceSimImage to Video Generation/GmeScoreImage to Video Generation/NexusScoreImage to Video Generation/NaturalScoreVideo/Total ScoreVideo/VenueVideo/AestheticsVideo/MotionVideo/FaceSimVideo/GmeScoreVideo/NexusScoreVideo/NaturalScoreVideo Generation/Total ScoreVideo Generation/VenueVideo Generation/AestheticsVideo Generation/MotionVideo Generation/FaceSimVideo Generation/GmeScoreVideo Generation/NexusScoreVideo Generation/NaturalScore

Statistics

Papers
8
Benchmarks
32

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Tasks

1 Image, 2*2 StitchiHuman-Domain Subject-to-VideoImage to Video GenerationOpen-Domain Subject-to-VideoSingle-Domain Subject-to-VideoText-to-Video GenerationVideoVideo Generation