This dataset contains the main result images (inputs and denoiser outputs) in lossless PFM format (compatible with GIMP 3.0.4 among others) for our paper “Statistical Error Reduction for Monte Carlo Rendering” (https://doi.org/10.1145/3757377.3763995). The directory names for the images correspond to the figure numbers in the paper and the supplementary document.

Furthermore, we provide additional materials (e.g., source code to reproduce the results) for our paper at https://www.cg.tuwien.ac.at/StatER.

Acknowledgments

We thank Thomas Auzinger for providing LaTeX plugins, José Dias Curto for support with confidence intervals, and Markus Schütz for assistance with the CUDA implementation. We also thank the creators of the scenes we used: Benedikt Bitterli for “Veach, Bidir Room” (Figs. 1, S12), “Cornell Box” (Fig. 2), and “Fur Ball” (Fig. 12); Jay-Artist for “Country Kitchen” (Figs. 4, 5, 10, S2, S10, S16); Mareck for “Contemporary Bathroom” (Figs. 7, 14, S13); thecali for “4060.b Spaceship” (Fig. 9); piopis for “Old Vintage Car” (Fig. 13); Cem Yuksel for “Straight Hair” (Fig. S4) and “Curly Hair” (Fig. S5); UP3D for “Little Lamp” (Fig. S6); axel for “Glass of Water” (Fig. S7); MrChimp2313 for “Victorian Style House” (Fig. S8); NovaAshbell for “Japanese Classroom” (Fig. S9); and Beeple for “Zero-Day” (Fig. S11). Statistical simulation studies were conducted using the Austrian Scientific Computing (ASC) infrastructure. This work has been funded by the Vienna Science and Technology Fund (WWTF) [Grant ID: 1047379/ICT22028]. This research was funded in whole or in part by the Austrian Science Fund (FWF) [10.55776/F77]. For open-access purposes, the author has applied a CC BY public copyright license to any author-accepted manuscript version arising from this submission. The authors acknowledge TU Wien Bibliothek for financial support through its Open Access Funding Programme.