A Survey on Future Frame Synthesis: Bridging Deterministic and Generative Approaches

Abstract

Future Frame Synthesis (FFS, aka Video Frame Prediction) focuses on generating future frame sequences conditioned on existing content. This survey provides a comprehensive review of existing research on FFS, covering commonly used datasets and representative algorithms. We discuss key challenges and trace the evolution of FFS in computer vision, particularly the shift from deterministic to generative approaches. Our taxonomy outlines major advances and methodological shifts, emphasizing the rising significance of generative models in producing realistic and diverse predictions. This survey offers a comprehensive analysis of current research and, moreover, suggests promising avenues for future exploration in this ever-changing domain.

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