The "Video Trends 2026" survey released by Germany's state media regulators shows that 79% of respondents have encountered AI-generated or heavily modified videos online, most concentrated on TikTok and Instagram; among users who encountered such content, 68% mistook it for real at least once. 81% of respondents said they now more often doubt the authenticity of videos, about 90% demand mandatory labeling of AI content, and 83% support banning certain forms of deepfakes.
Google Research has released a multi-agent framework for automatically generating temporally coherent long-form video narratives, aimed at alleviating identity drift and cascading failure issues in existing linear pipelines. The framework is built on Gemini and Veo and comprises four parts: AI video co-director, CANVAS, A2RD, and VQQA, which are respectively responsible for creative orchestration, visual storyboarding, long-duration generation, and closed-loop optimization. Evaluations show that AI video co-director achieves a peak quality score of 81.4 on GenAD-Bench, and A2RD can generate ten-minute-long videos while maintaining character and environment consistency. No further progress has been disclosed at present.
Google Research has released a multi-agent framework for automatically generating temporally coherent long-form video narratives, aimed at alleviating identity drift and cascading failure issues in existing linear pipelines. The framework is built on Gemini and Veo and comprises four parts: AI video co-director, CANVAS, A2RD, and VQQA, which are respectively responsible for creative orchestration, visual storyboarding, long-duration generation, and closed-loop optimization. Evaluations show that
Google Research has released a unified multi-agent framework for automatically generating temporally coherent long-video narratives, addressing identity drift and cascading failures in existing linear pipelines. Built on top of Gemini and Veo as an orchestration layer, the framework consists of four parts: AI video co-director uses multi-armed bandits for global creative search, CANVAS plans multi-shot visual continuity through persistent visual memory, A²RD generates segment by segment autoregressively while maintaining multimodal video memory, and VQQA uses visual question answering to generate semantic gradients for closed-loop prompt optimization. Evaluations show that AI video co-director reaches a peak quality score of 81.4 on GenAD-Bench, CANVAS improves scene-reappearance continuity on ST-Bench and HardContinuityBench, A²RD reduces layout drift on VBench-Long and LVBench-C, and VQQA achieves quality gains on T2V-CompBench, VBench2, and VBench-I2V.
Google Research has released a unified multi-agent framework for automatically generating temporally coherent long-video narratives, addressing identity drift and cascading failures in existing linear pipelines. Built on top of Gemini and Veo as an orchestration layer, the framework consists of four parts: AI video co-director uses multi-armed bandits for global creative search, CANVAS plans multi-shot visual continuity through persistent visual memory, A²RD generates segment by segment autoregr
Google Research has released a multi-agent framework for automatically generating temporally coherent long-form video narratives, aimed at alleviating identity drift and cascading failure issues in existing linear pipelines. The framework is built on Gemini and Veo and comprises four parts: AI video co-director, CANVAS, A2RD, and VQQA, which are respectively responsible for creative orchestration, visual storyboarding, long-duration generation, and closed-loop optimization. Evaluations show that AI video co-director achieves a peak quality score of 81.4 on GenAD-Bench, and A2RD can generate ten-minute-long videos while maintaining character and environment consistency. No further progress has been disclosed at present.
