Inference-based GAN for Long Video Generation
Published:Dec 25, 2025 20:14
•1 min read
•ArXiv
Analysis
This paper addresses the challenge of generating long, coherent videos using GANs. It proposes a novel VAE-GAN hybrid model and a Markov chain framework with a recall mechanism to overcome the limitations of existing video generation models in handling temporal scaling and maintaining consistency over long sequences. The core contribution lies in the memory-efficient approach to generate long videos with temporal continuity and dynamics.
Key Takeaways
- •Proposes a VAE-GAN hybrid model for video generation.
- •Introduces a Markov chain framework with a recall mechanism to generate long videos.
- •Addresses the challenge of temporal scaling and maintaining consistency in long video sequences.
- •Focuses on memory-efficient generation of long videos.
Reference
“Our approach leverages a Markov chain framework with a recall mechanism, where each state represents a short-length VAE-GAN video generator. This setup enables the sequential connection of generated video sub-sequences, maintaining temporal dependencies and resulting in meaningful long video sequences.”