Full quality images for the Supplementary Material for Fast 3D Gaussian Splatting Rendering via Easily Integrable Improvements

This dataset contains the full quality (full resolution, lossless compression) renders and ground truth images for the Supplementary Material for Fast 3D Gaussian Splatting Rendering via Easily Integrable Improvements, by Laurens Diels, Michiel Vlaminck, Wilfried Philips and Hiep Luong (DOI: 10.1109/lsp.2024.3521379).For information on the file naming scheme, we refer to __README__.txt inside of the zip file.References:* 3D Gaussian Splatting: B. Kerbl, G. Kopanas, T. Leimkühler, and G. Drettakis, “3D Gaussian Splatting for Real-Time Radiance Field Rendering,” ACM Trans. Graph., vol. 42, no. 4, pp. 139–1, 2023. https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/* Mip-NeRF 360 (Bicycle, Garden, Stump): J. T. Barron, B. Mildenhall, D. Verbin, P. P. Srinivasan, and P. Hedman, “Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 5470–5479. https://jonbarron.info/mipnerf360/* Tanks and Temples (Train): A. Knapitsch, J. Park, Q.-Y. Zhou, and V. Koltun, “Tanks and Temples: Benchmarking Large-Scale Scene Reconstruction,” ACM Transactions onGraphics (ToG), vol. 36, no. 4, pp. 1–13, 2017.https://www.tanksandtemples.org/* Deep Blending (Playroom): P. Hedman, J. Philip, T. Price, J.-M. Frahm, G. Drettakis, and G. Brostow, “Deep Blending for Free-Viewpoint Image-Based Rendering,” ACM Transactions on Graphics (ToG), vol. 37, no. 6, pp. 1–15, 2018.http://visual.cs.ucl.ac.uk/pubs/deepblending/