You're currently viewing an old version of this dataset. To see the current version, click here.

EscherNet: A Generative Model for Scalable View Synthesis

EscherNet is a multi-view conditioned diffusion model designed for scalable view synthesis. It leverages Stable Diffusion's 2D architecture empowered by the innovative Camera Positional Embedding (CaPE), EscherNet adeptly learns implicit 3D representations from varying number of reference views, achieving consistent 3D novel view synthesis.

Data and Resources

This dataset has no data

Cite this as

Xin Kong, Shikun Liu, Xiaoyang Lyu, Marwan Taher, Xiaojuan Qi, Andrew J. Davison (2024). Dataset: EscherNet: A Generative Model for Scalable View Synthesis. https://doi.org/10.57702/qhbmtyy6

Private DOI This DOI is not yet resolvable.
It is available for use in manuscripts, and will be published when the Dataset is made public.

Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2402.03908
Author	Xin Kong
More Authors	Shikun Liu Xiaoyang Lyu Marwan Taher Xiaojuan Qi Andrew J. Davison
Homepage	https://kxhit.github.io/EscherNet