arXiv AI
Beyond Coherence: Benchmarking Professional Editing-Technique Execution in Multi-Shot Audio-Video Generation
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AVENUE: Audio-Video EditiNg Understanding and Evaluation
AVENUE is a new benchmark and evaluation framework for audio‑video editing that includes 1,291 source clips and 7,957 editing instructions covering audio‑targeted, video‑targeted, and coupled edits. It introduces a sample‑specific, modality‑aware evaluation that specifies the intended change and the content that must remain unchanged. The study applies this framework to joint, sequential, and separate editing models, revealing that existing models often alter unintended modalities, highlighting a key challenge in controllable AV editing.
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OmniEdit-Bench: A Comprehensive Benchmark for Instruction-based Video Editing
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Thinking on Shots: Consistent Multi-Shot Video Editing with Agentic Reasoning
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Hugging Face Trending Papers
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Thinking on Shots: Consistent Multi-Shot Video Editing with Agentic Reasoning
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arXiv AI
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CoVEBench: Can Video Editing Models Handle Complex Instructions?
arXiv:2606. 08415v1 Announce Type: cross Abstract: While recent text-guided video editing models excel at elementary tasks (e.
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CoinVE-200K: A Large-Scale High-Quality Dataset for Compositional Instruction-Guided Video Editing
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