系统梳理2022年后AI在创意产业的突破与融合应用
Advances in Artificial Intelligence: A Review for the Creative Industries
- 整合生成式AI、大模型与扩散模型,重构内容创作全流程
- 实现文本到图像/视频生成、实时3D重建等新能力
- 适合关注AI与创意融合的研究者与从业者
自2022年以来,人工智能在生成式AI、大型语言模型(LLMs)和扩散模型推动下取得变革性进展,深刻重塑创意产业。本文填补现有综述未涵盖近期突破及跨创作流程整合影响的空白,系统回顾2022年至今成熟或涌现的AI技术,涵盖内容创作、信息分析、后期增强、压缩与质量评估等环节。我们记录了变换器、大语言模型、扩散模型与隐式神经表示如何在文本到图像/视频生成、实时3D重建及统一多任务框架中建立新能力,使AI从辅助工具转变为核心创作技术。此外,我们分析统一框架集成多任务趋势,替代专用解决方案;批判性审视人机协作演变,强调人类在创意导向与缓解幻觉中的关键作用。最后,识别版权争议、偏见缓解、计算需求及监管框架缺失等新兴挑战。本综述为研究者与实践者提供当前创意应用中AI能力、局限与未来方向的全面理解。
原文摘要 · Abstract (English)
Artificial intelligence (AI) has undergone transformative advances since 2022, particularly through generative AI, large language models (LLMs), and diffusion models, fundamentally reshaping the creative industries. However, existing reviews have not comprehensively addressed these recent breakthroughs and their integrated impact across the creative production pipeline. This paper addresses this gap by providing a systematic review of AI technologies that have emerged or matured since our 2022 review, examining their applications across content creation, information analysis, post-production enhancement, compression, and quality assessment. We document how transformers, LLMs, diffusion models, and implicit neural representations have established new capabilities in text-to-image/video generation, real-time 3D reconstruction, and unified multi-task frameworks-shifting AI from support tool to core creative technology. Beyond technological advances, we analyze the trend toward unified AI frameworks that integrate multiple creative tasks, replacing task-specific solutions. We critically examine the evolving role of human-AI collaboration, where human oversight remains essential for creative direction and mitigating AI hallucinations. Finally, we identify emerging challenges including copyright concerns, bias mitigation, computational demands, and the need for robust regulatory frameworks. This review provides researchers and practitioners with a comprehensive understanding of current AI capabilities, limitations, and future trajectories in creative applications.
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