Dataset · Hugging Face

AIPeanutman/OmitI2V

Name: OmitI2V
Creator: AIPeanutman
License: apache-2.0
Keywords: task_categories:image-to-video, language:en, license:apache-2.0, size_categories:n<1K, format:imagefolder, modality:image, library:datasets, library:mlcroissant, arxiv:2512.01334, region:us, text-to-video, image-to-video, text-guided-image-to-video, benchmark, prompt-adherence

OmitI2V OmitI2V is a benchmark for evaluating semantic fidelity (prompt adherence) in text-guided image-to-video (TI2V) generation, focusing on prompts that require substantial edits to the reference image — object addition, deletion, and modification. It is the benchmark introduced in AlignVid: Taming Visual Dominance via Training-Free Attention Modulation in Text-guided Image-to-Video Generation (ICML 2026). 📄 Paper https://arxiv.org/abs/2512.01334 💻 Code… See the full description on the dataset page: https://huggingface.co/datasets/AIPeanutman/OmitI2V.

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Author / organization	AIPeanutman
License (as declared)	apache-2.0
Downloads	394 (as reported by Hugging Face)
Likes	0
Created	25 May 2026
Last updated at source	5 August 2026

text-to-videoimage-to-videotext-guided-image-to-videobenchmarkprompt-adherencesemantic-fidelityvideo-generation

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