Kaifeng Zhang
@kaiwynd • 2,727 subscribers
PhD student at Columbia University
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🧵 Evaluating robot policies in the real world is slow, expensive, and hard to scale. During my internship at SceniX AI this summer, we had many discussions around the two key questions: how accurate must a simulator be for evaluation to be meaningful, and how do we get there? Our new framework, Real2Sim-Eval, takes a step toward that answer. By combining Gaussian Splatting for photorealistic rendering and soft-body digital twins for realistic dynamics, we make simulation predictive of real-world performance. 👉
Kaifeng Zhang60,256 просмотров • 6 месяцев назад
Can we learn a 3D world model that predicts object dynamics directly from videos? Introducing Particle-Grid Neural Dynamics: a learning-based simulator for deformable objects that trains from real-world videos. Website: ArXiv: Code: Demo: To appear at #RSS2025
Kaifeng Zhang45,946 просмотров • 11 месяцев назад
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