Atlas世界模型通过新视图预测统一像素生成与重建
Next view prediction is the key to Atlas, enabling us to unify pixel-level generation and reconstruc...
李飞飞团队发布Atlas世界模型，用新视图预测技术把3D空间拍摄成本降低100倍，只需3张照片就能完成原本300张照片的工作。
Atlas是由李飞飞等人开发的全新空间智能世界模型，基于新视图预测技术。该模型将计算机视觉领域分离了半个世纪的像素生成与像素重建问题首次统一起来。Atlas将空间数字化的成本降低了50到100倍，原本需要100到300张照片才能完成的空间3D表示，现在仅需3张照片即可实现。
Next view prediction is the key to Atlas, enabling us to unify pixel-level generation and reconstruc...
Next view prediction is the key to Atlas, enabling us to unify pixel-level generation and reconstruction. @jcjohnss @BenMildenhall @martin_casado and I had a deeper discussion on some of the most exciting technical innovations of Atlas, our newly released world model for spatial intelligence! a16z @a16z World Labs co-founders Fei-Fei Li, Justin Johnson, Ben Mildenhall, and a16z's Martin Casado on Atlas, a world model for spatial intelligence: LLMs are built on next token prediction. Video models are built on next frame prediction. Atlas is built on new view prediction, and it's the first model to unify pixel generation and pixel reconstruction, two problems computer vision has kept in separate tracks for half a century. The practical result is a 50 to 100x reduction in what it takes to digitally capture a 3D representation of a space. Previously, you needed 100 to 300 photos of a single room. Atlas can work from just three. In this conversation, they get into the slow motion shot from The Matrix that took hundreds of cameras and now takes three iPhones, the overnight Slack message that made them bet the company in five seconds, why robotics is bottlenecked on data rather than chips, and the case that new view prediction is AI-complete. 00:00 Intro 01:50 The Matrix slow motion scene now takes three iPhones 02:48 Why new view prediction is the primitive 07:10 Unifying generation and reconstruction 11:15 Gaussian splats became the bottleneck 14:17 Dense capture used to mean 300 photos 17:30 Why reconstruction needs generation to fill the gaps 18:44 The LLM lesson image models missed 23:39 The video that made them go all in 28:04 3D design is 95% revisions 30:50 The problem in robotics is data, not chips 32:48 Why a robot policy can't be trained like an image model 34:44 When the simulator becomes the planner 36:45 Frozen time required footage full of movement 40:57 Why new view prediction is AI-complete 42:43 Nature gave animals eyes but not trees YouTube: youtube.com/watch?v=qn1QDD… @drfeifei @jcjohnss @BenMildenhall @theworldlabs @martin_casado Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 5 🔄 7 ❤️ 61 👀 8223 📊 10 ⚡
