AI RESEARCH
SLVMEval: Synthetic Meta Evaluation Benchmark for Text-to-Long Video Generation
arXiv CS.AI
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ArXi:2603.29186v1 Announce Type: cross This paper proposes the synthetic long-video meta-evaluation (SLVMEval), a benchmark for meta-evaluating text-to-video (T2V) evaluation systems. The proposed SLVMEval benchmark focuses on assessing these systems on videos of up to 10,486 s (approximately 3 h). The benchmark targets a fundamental requirement, namely, whether the systems can accurately assess video quality in settings that are easy for humans to assess. We adopt a pairwise comparison-based meta-evaluation framework.