AI视频生成终于记住场景了：绕到背后也不穿帮
现在的AI视频生成，镜头一转就“失忆”——刚才看到的场景细节全忘光，换个视角就穿帮。WorldCrafter给视频生成模型装了一个“3D记忆”：它把之前看过的画面压缩成一组带视角标签的令牌，你要求从哪个角度看，它就按那个角度重新组织记忆再生成下一帧，不需要显式的深度计算。结果就是：从一张图或一句话出发，你可以像玩游戏一样在场景里连续探索一分钟，绕到物体背后、拉近拉远，场景的布局和细节都保持连贯，镜头控制也更准。它不是你明天就能用的工具，但这是视频生成从“单镜头魔术”走向“可探索虚拟世界”的关键一步。
📄 原文摘要(英文)
Video world models enable interactive exploration of dynamic environments, yet struggle to respect prior observations over long horizons and across viewpoints. We present WorldCrafter, a video world model that learns a camera-queryable implicit 3D-aware memory for this purpose. The key insight is to let the requested viewpoint shape how multi-view evidence is compressed into the video generator's limited token budget. Trained jointly with the video generator, a memory encoder and pose-conditioned readout module integrate historical observations into a fixed set of target view-specific tokens before denoising, without explicit depth-based correspondences. By combining this memory with recent temporal context and few-step distillation, WorldCrafter enables streaming scene exploration from a single input image or text prompt. Experiments across static and dynamic scenes show substantial gains in long-horizon consistency and camera-control accuracy while preserving visual quality during minute-scale exploration.