NeuIDO: Neural Intrinsic Dynamics Operator for Physics-Informed 4D World Models
cs.CV
Submitted: 2026-09-21
Updated: 2026-09-21
Comments: Accepted by ECCV 2026; Project Page: https://github.com/JiajingLin/NeuIDO
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Revisiting Feature Prediction for Learning Visual Representations from Video
- TransDreamer: Reinforcement Learning with Transformer World Models
- Dream to Control: Learning Behaviors by Latent Imagination
- Mastering Atari with Discrete World Models
- Mastering Diverse Domains through World Models
- GAIA-1: A Generative World Model for Autonomous Driving
- LoRA: Low-Rank Adaptation of Large Language Models
- How Far is Video Generation from World Model: A Physical Law Perspective
- 3D and 4D World Modeling: A Survey
- A Library for Learning Neural Operators
- Phy124: Fast Physics-Driven 4D Content Generation from a Single Image
- Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion
- DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
- Transformers are Sample-Efficient World Models
- Transformer-based World Models Are Happy With 100k Interactions
- GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving
- Digital Gene: Learning about the Physical World through Analytic Concepts
- Learning Interactive Real-World Simulators
- RoboDreamer: Learning Compositional World Models for Robot Imagination
- Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond
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