Shaif Chowdhury, Moshiur Rahman Tonmoy · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28524 · open-access PDF
Beberapa kemajuan baru-baru ini telah menimbulkan kekhawatiran tentang reproduksi konten visual yang dilindungi hak cipta. Namun, deteksi kebocoran hak cipta dalam video yang dihasilkan tetap sebagian besar belum dijelajahi. Dalam makalah ini, kami memperkenalkan set data benchmark baru untuk deteksi kebocoran hak cipta, yang terdiri dari 50 konsep yang dilindungi hak cipta, masing-masing dengan 5 gambar. Untuk setiap konsep, kami memiliki 5 video yang dibuat menggunakan model pembuatan gambar + prompt video dan model pembuatan video hanya dengan prompt.
Machine translation (Meta M2M100); the English original follows.
Video generation models can create realistic-looking video footage from images and text prompts. Some of the recent advances have raised concerns about the reproduction of copyrighted visual content. However, copyright leakage detection in generated videos remains largely unexplored. In this paper, we introduce a new benchmark data set for copyright leakage detection, comprising 50 copyrighted concepts, each with 5 images. For each concept, we have 5 videos created using the image+prompt video generation model and the prompt-only video generation model. Following that, we develop an AI toolset
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