July 19, 2024Open Access

Unlearning Concepts from Text-to-Video Diffusion Models

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Authors

SLShiqi LiuXi'an Jiaotong University YTYihua Tan

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Implication

Novel method unlearns copyrighted content in text-to-video diffusion models, enabling safer media generation.

Key Points

Our method successfully unlearns copyrighted cartoon characters and artist styles, enhancing content safety.
The unlearning process takes about 100 seconds on an RTX 3070, demonstrating efficiency and speed.
We utilize few-shot unlearning to optimize the text encoder, allowing for quick adaptation in video generation workflows soon after model training starts again or retries occur in applications relying on these methods for their content production needs swiftly and effectively overcoming past limitations regarding resource constraints and scalability, enabling proper adjustments without extensive delays where time is critical for creators and users alike looking to produce engaging video material in today's fast-paced digital landscape while maintaining strict adherence to copyright regulations set forth for responsible usage of media formats today in online and visual domains alike across trends shaping our creative industries steadily over time as they evolve constantly nowadays regardless of shifts in preferences or societal standards surrounding communication mediums overall, especially within digital environments prompted by rapid technological advancements across the board today that redefine artistic expression continuously moving forward through innovative tools available widely when navigating current landscapes developing year by year; and they each highlight necessary changes needed to advance this field effectively with all results evaluated while aiming for responsiveness overall across ecosystems built around empowering creatives towards innovative output continually recognized as valuable across various domains collaboratively over extended periods that honor artistic integrity above all else by basing ideals founded on ethical principles guiding foundational practices within these exciting fields ahead!

Cite This Study

Liu et al. (2024) studied this question.

synapsesocial.com/papers/68e5fc83b6db643587590b95 https://doi.org/10.48550/arxiv.2407.14209

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Unlearning Concepts from Text-to-Video Diffusion Models

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Implication

Key Points

Cite This Study

Unlearning Concepts from Text-to-Video Diffusion Models

Discussion

Member takes

Implication

Key Points

Cite This Study

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