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Mip-NeRF 360 and Tanks & Temples datasets
The Mip-NeRF 360 and Tanks & Temples datasets are used to evaluate the performance of the Pixel-GS method. -
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... -
Neural scene flow fields for space-time view synthesis of dynamic scenes
A neural scene flow fields for space-time view synthesis of dynamic scenes. -
LLFF dataset
The dataset used in the paper is the LLFF dataset, which contains real-world scenes and is used for training and testing the proposed neural radiance field model. -
RealEstate-10K
The dataset used in the paper for training and testing the NeRF model. -
DTU dataset
The DTU dataset is a large-scale dataset for multi-view stereo depth inference. It contains over 100 scans taken under 7 different lighting conditions and fixed camera...