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Seventy3: 用NotebookLM将论文生成播客,让大家跟着AI一起进步。
今天的主题是:GenMAC: Compositional Text-to-Video Generation with Multi-Agent CollaborationSummary
The paper introduces GENMAC, a novel multi-agent framework for generating complex, dynamic videos from text prompts. GENMAC uses a three-stage iterative process (DESIGN, GENERATION, REDESIGN) with specialized agents in the REDESIGN stage to verify, suggest corrections, and refine the generated video. This multi-agent approach overcomes limitations of single-agent methods in handling complex spatiotemporal relationships and object interactions. The system's effectiveness is demonstrated through quantitative and qualitative comparisons against state-of-the-art models on the T2V-CompBench benchmark, showcasing superior performance in compositional text-to-video generation. Ablation studies highlight the importance of each component within the framework.
原文链接:https://arxiv.org/abs/2412.04440
Seventy3: 用NotebookLM将论文生成播客,让大家跟着AI一起进步。
今天的主题是:GenMAC: Compositional Text-to-Video Generation with Multi-Agent CollaborationSummary
The paper introduces GENMAC, a novel multi-agent framework for generating complex, dynamic videos from text prompts. GENMAC uses a three-stage iterative process (DESIGN, GENERATION, REDESIGN) with specialized agents in the REDESIGN stage to verify, suggest corrections, and refine the generated video. This multi-agent approach overcomes limitations of single-agent methods in handling complex spatiotemporal relationships and object interactions. The system's effectiveness is demonstrated through quantitative and qualitative comparisons against state-of-the-art models on the T2V-CompBench benchmark, showcasing superior performance in compositional text-to-video generation. Ablation studies highlight the importance of each component within the framework.
原文链接:https://arxiv.org/abs/2412.04440