(3/3) As for colorization, we use color images manually colorized by artist Martin Oeggerli, we project colors onto 3D space with estimated depths and take the colors to create supervision, and also use feature loss employed by Ref-NPR to estimate invisible areas of input colors.

(2/3) Our work utilizes Scanning Electron Microscopy (SEM) images of pollen. Two stages: grayscale novel view synthesis and colorization. The grayscale scene is represented by 2DGS, where poses are estimated using perspective projection with exceptionally long focal lengths.

Thrilled to share our work: 𝐀𝐫𝐂𝐒𝐄𝐌: Artistic Colorization of SEM Images via Gaussian Splatting
Novel view synthesis of scanning electron microscopy images and Conditional colorization.
📝 arXiv: arxiv.org/abs/2410.21310
🎨Project page: ronly2460.github.io/ArCSEM
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