arXiv:2606. 30292v1 Announce Type: new Abstract: We present DreamForge-World 0.
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.
arXiv:2607.26694v3 Announce Type: replace Abstract: We present Visko Orbis 1.0, a Live Model for real-time, interactive long video generation. Users can change the prompt at any moment during generat...
arXiv:2508.13009v5 Announce Type: replace Abstract: Recent advances in interactive video generations have demonstrated diffusion model's potential as world models by capturing complex physical dynami...
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.
arXiv:2607. 19191v1 Announce Type: cross Abstract: We present ABot-World-0, an action-conditioned video world model for real-time, long-horizon closed-loop interaction, supported by a multi-source data infrastructure spanning AAA games, simulation engines, and internet videos to learn controllable world dynamics.
The paper introduces a large‑scale synthetic data pipeline built on Unreal Engine to generate action‑conditioned, multi‑view video for training world models. The system operates in two stages: real‑time physics simulation records trajectories, then offline rendering produces high‑quality video. It includes a distributed production framework with task partitioning, automated filtering, and a 25‑server cluster, yielding over 2,600 hours of 1080p and 6,000 hours of 720p video from 429 levels and 40 characters.
arXiv:2604.08995v3 Announce Type: replace Abstract: With the advancement of interactive video generation, diffusion models have increasingly demonstrated their potential as world models. However, exi...
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...
arXiv:2605.30263v2 Announce Type: replace Abstract: Recent video diffusion foundation models have achieved remarkable progress in high-quality video generation, yet turning them into real-time intera...
arXiv:2606. 10135v1 Announce Type: cross Abstract: Transitioning bidirectional video diffusion models into an autoregressive paradigm improves the interactivity of video world models, but existing causal pipelines need many stages (control fine-tuning, autoregressive training, causal initialization, few-step distillation) and still trail bidirectional models in quality due to error accumulation.
arXiv:2609.00610v1 Announce Type: new Abstract: Current 4D generation paradigms are often bottlenecked by a sequential decoupling design: video is generated first, followed by 3D reconstruction, lead...
arXiv:2607.08098v2 Announce Type: replace Abstract: Event cameras are increasingly adopted in embodied perception for their microsecond temporal resolution, high dynamic range, and resilience to moti...