Learning Video Dynamics with Predictive Differentiable Rendering

arXiv cs.CV1mo4 min read

arXiv:2606.31050v1 Announce Type: new Abstract: How to accurately predict a high-fidelity future world? While the visual world is inherently continuous, existing deterministic video prediction models operate in discrete pixel space and are mainly optimized with pixel-wise mean squared error (MSE), which often leads to over-smoothed predictions and a lack of fine-grained visual details. To address these limitations, we propose Predictive Differentiable Rendering (PDR), a novel end-to-end video prediction paradigm that bridges the gap between discrete and continuous representations. Inspired by

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Learning Video Dynamics with Predictive Differentiable Rendering

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