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This paper presents EventSeeColor, which uses event-reconstructed grayscale and aligned events to jointly guide a diffusion colorizer that achieves the best structural similarity, learned perceptual scores, and chromatic-region color difference among the external methods.
Aes3D, the first systematic framework for assessing the aesthetics of 3D neural rendering scenes, is proposed, and Aes3DGSNet, a lightweight model that directly predicts scene-level aesthetic scores from 3DGS representations, is presented, a lightweight model that operates solely on 3D Gaussian primitives.
FracEvent, an event simulator that models this pixel-level lifecycle with fractional-relaxation voltage dynamics, improves the temporal structure of generated events and achieves stronger downstream-transfer results than competing simulator baselines, showing its practical value for event-camera simulation.
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