CC BY 4.0Sinha, Saptarshi NeilSaptarshi NeilSinhaKühn, JuliusJuliusKühnGraf, HolgerHolgerGrafWeinmann, MichaelMichaelWeinmann2024-10-092024-10-092024https://publica.fraunhofer.de/handle/publica/477034https://doi.org/10.24406/publica-373610.1145/3665318.367715110.24406/publica-3736Spectral rendering accurately simulates light-material interactions by considering the entire light spectrum, unlike traditional rendering methods that use limited color channels like RGB. This technique is particularly valuable in industries to assess visual quality before production. Moreover, Spectral imaging finds extensive applications in fields like agriculture for plant disease detection, cultural heritage for preservation, forensic science, environment monitoring and medical science among others. Advances in generating novel views from images have been achieved through methods like NERF and Gaussian splatting, which outperforms others in terms of quality. This paper introduces a web-based viewer built on the Viser framework for visualizing and comparing cross-spectral Gaussian splats from different views and during various training stages. This viewer supports real-time collaboration and comprehensive visual comparison, enhancing user experience in spectral data analysis. We conduct a user study and performance analysis to confirm its effectiveness and usability for different application scenarios, while also proposing potential enhancements for increased functionality.enBranche: Automotive IndustryBranche: Information TechnologyBranche: Cultural and Creative EconomyResearch Line: Computer graphics (CG)Research Line: Computer vision (CV)Research Line: Machine learning (ML)LTA: Monitoring and control of processes and systemsLTA: Generation, capture, processing, and output of images and 3D modelsDeep learningCultural heritageMultispectral imagesScene understandingconference paper