1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2025
Rethinking Video Tokenization: A Conditioned Diffusion-based Approach
Nianzu Yang, Pandeng Li, Liming Zhao +8
Existing video tokenizers typically use the traditional Variational Autoencoder (VAE) architecture for video compression and reconstruction. However, to achieve good performance, i…
cs.CV2024★ 1 cited
Improved Video VAE for Latent Video Diffusion Model
Pingyu Wu, Kai Zhu, Yu Liu +4
Variational Autoencoder (VAE) aims to compress pixel data into low-dimensional latent space, playing an important role in OpenAI's Sora and other latent video diffusion generation…