arXiv Computer Vision

Magpie: Real-Time World Renderer for Interactive Games

Magpie is a real‑time generative world‑rendering system designed for interactive games. It decouples gameplay execution from visual generation, allowing designers to define scenes and rules in a game engine while a separate render server produces visual output from the engine’s white‑box frames. This approach preserves gameplay designability and reproducibility, and reduces early prototype dependence on finished visual assets.

Hugging Face Trending Papers
Aug 27

Magpie: Real-Time World Renderer for Interactive Games

Magpie is a real‑time generative world‑rendering system that decouples gameplay execution from visual generation. Designers set up scenes and rules in a game engine, which handles player actions and world state, while a separate Render Server produces visual output from the engine’s white‑box frames. This approach lets developers create interactive games without needing fully finished visual assets early in the prototype stage.

arXiv Computer Vision
Sep 10

Programmable World Model

arXiv:2609.10540v1 Announce Type: new Abstract: Recent video world models generate increasingly realistic and interactive visual experiences, yet lack reliable mechanisms for maintaining persistent w...

By Zheng-Hui Huang, Guixu Lin, Jiacheng Lin, Yi-Chuan Huang, Ruihan Yu, Muyao Niu, Siqi Yang, Yu-Lun Liu, Yung-Yu Chuang, Kaipeng Zhang, Zhixiang Wang
arXiv AI
Aug 11

VideoCoCo: Code-as-CoT for Physically-Consistent Video Generation via an Agentic Dual-Engine System

arXiv:2607. 27380v2 Announce Type: replace-cross Abstract: Text-to-video models have achieved remarkable visual quality, yet they still struggle to generate physically consistent dynamics because the temporal evolution of a scene must be inferred implicitly from a highly compressed text prompt.

By Haodong Li, Tianfei Ren, Xiaoxiao Ma, Chunmei Qing, Zhen Fang, Sipeng He, Ziyu Guo, Haoyu Wu, Juanxi Tian, Yihang Zou, Ruichuan An, Dongzhi Jiang, Boxue Yang, Ji Xie, Xu Huang, Wenhao Yan, Jialv Zou, Zhengrong Yue, Yaxin Luo, Xiaotong Li, Yuzhu Wang, Junyan Ye, Jinjing Zhao, Zehui Chen, Lin Chen, Renye Yan, Feng Zhao, Pheng-Ann Heng
arXiv AI
Jul 22

AlayaWorld: Interactive Long-Horizon World Modeling -- Full Technical Report

arXiv:2607. 18367v1 Announce Type: new Abstract: Unlike conventional video game development, which relies on labor-intensive pipelines for asset production, animation, physics, and programming, video world models generate interactive environments from user inputs instantly.

By AlayaWorld Team, Kaipeng Zhang, Chuanhao Li, Yifan Zhan, Yongtao Ge, Yuanyang Yin, Jiaming Tan, Kang He, Liaoyuan Fan, Mingliang Zhai, Ruicong Liu, Xiaojie Xu, Xuangeng Chu, Zhen Li, Zhengyuan Lin, Zhixiang Wang, Zian Meng, Zihui Gao
arXiv Computer Vision
2d ago

Waypoint-1.5: A Real-Time Video World Model for Consumer Hardware

Waypoint‑1.5 is a real‑time diffusion world model designed for interactive video generation on consumer‑grade hardware. It is pre‑trained on 100,000 hours of control‑aligned video game footage and can generate playable video conditioned on full keyboard and mouse input. The system offers two resolution variants, distinguishes rendered FPS, latent FPS, and control rate, and includes a detailed data pipeline, architecture, training methodology, and runtime system.

By Rajit Rajpal, Shahbuland Matiana, Liew Wei Pyn, Anmol Agarwal, Ryan Craig, Andrew Lapp, Mithun Hunsur, Sami BuGhanem, Scottie Fox, Aaron Sanders Carson Poole, Irene Park, Dave Rossi, Spencer Frazier, Louis Castricato
arXiv AI
Sep 2

Solaris: Towards Interfaces That Are Generated, Not Coded

arXiv:2609.00776v1 Announce Type: cross Abstract: Digital interfaces are traditionally implemented through intermediate representations such as code, requiring their appearance and behavior to be spe...

By Yuval Alaluf, Omri Avrahami, Guy Bukchin Leshem, Michal Geyer, Kfir Goldberg, Elad Richardson, Diego Alarc\'on, Alejandro Alvarez, Cole Garry, Anastasis Germanidis, Tenaya Goldsen, Corina Gurau, Robin Kahlow, Joel Kwartler, Kathleen Lewis, Alejandro Matamala Ortiz, Eugene McMahon, Thon Prom, Sarah Saltonstall-Wurm, Jamie Umpherson, Hudson Yeo
arXiv AI
Aug 11

Population-Scalable Multi-Agent World Modeling

arXiv:2608. 08600v1 Announce Type: cross Abstract: World models have recently achieved impressive progress in visual prediction and interactive generation, but extending them to multi-agent environments introduces a fundamental scalability challenge.

By Renjie Zhao, Yuxiang Wu, Mingyu Zhang, Jiaxin Li, Sisi Li, Yimin Sheng, Tianxi Tan, Zhenkai Zhang, Jianyi Zhu, Yong-Lu Li