Paper of the DayarXiv:2605.12013
L2P: Unlocking Latent Potential for Pixel Generation
Zhennan Chen, Junwei Zhu, Xu Chen, Jiangning Zhang, Jiawei Chen, Zhuoqi Zeng, Wei Zhang, Chengjie Wang, Jian Yang, and Ying Tai
Computer Vision and Artificial Intelligence
L2P studies a latent-to-pixel transfer approach for pixel-space diffusion models. The authors freeze intermediate layers from pretrained latent diffusion models, train shallow layers for latent-to-pixel transfer, and report native high-resolution generation without the usual VAE bottleneck.
Why it matters: A useful paper for thinking about how much prior knowledge can be transferred without retraining an entire generative model from scratch.
