Decoupled Drift-Diffusion World Models for Consistent Future Frame Prediction
cs.CV
Submitted: 2026-10-13
Updated: 2026-10-13
Comments: 32 pages, 18 figures, 7 tables. Project page: https://anton-arapin.github.io/d3wm-site
Project page: https://anton-arapin.github.io/d3wm-site
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- World Simulation with Video Foundation Models for Physical AI
- One-Shot Refiner: Boosting Feed-forward Novel View Synthesis via One-Step Diffusion
- VideoGPA: Distilling Geometry Priors for 3D-Consistent Video Generation
- Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability
- Dexterous World Models
- UniFuture: A 4D Driving World Model for Future Generation and Perception
- Learning Continuous-Time Dynamics by Stochastic Differential Networks
- Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit
- ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos
- IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
- World-consistent Video Diffusion with Explicit 3D Modeling
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