M.L. Molenaar
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11 records found
1
How Can We convert 2D Pixel Art into a 3D Voxel Representation
Exploring different 3D reconstruction algorithms on 2D pixel input
Pixel Fixer
Semi-Automated Techniques for Correcting Pixel Art
Related dataset 4TU.ResearchData: https://doi.org/10.4121/11446578-c1f3-474c-9cc4-6978a79b675b ...
Related dataset 4TU.ResearchData: https://doi.org/10.4121/11446578-c1f3-474c-9cc4-6978a79b675b
Procedural texturing for pixel art
Making pixel art resemble real materials
Optimal Multiple Importance Resampling
Optimal Spatial Reuse for Monte Carlo Light Transport Simulation
We introduce an extension to WRS (Weighted Reservoir Sampling), a key component of ReSTIR, to reduce the occurrence of duplicate samples in multi-sample reservoirs. Further, we show how samples from multiple reservoirs can be combined in an MIS-style estimator as opposed to resampling from them. Lastly, we combine these two components to compute optimal weights for this estimator in a similar vein to OMIS (Optimal Multiple Importance Sampling).
Our direct lighting proof of concept implementation demonstrates the efficacy of our WRS extension, lowering the variance of ReSTIR, particularly with difficult lighting arrangements. Further, our MIS-style estimator shows a significant improvement compared to ReSTIR. In problem domains where resampling produces a function value for integration, such as path tracing, this comes at no additional cost. Lastly however, optimal weights do not appear to be beneficial for our approach. ...
We introduce an extension to WRS (Weighted Reservoir Sampling), a key component of ReSTIR, to reduce the occurrence of duplicate samples in multi-sample reservoirs. Further, we show how samples from multiple reservoirs can be combined in an MIS-style estimator as opposed to resampling from them. Lastly, we combine these two components to compute optimal weights for this estimator in a similar vein to OMIS (Optimal Multiple Importance Sampling).
Our direct lighting proof of concept implementation demonstrates the efficacy of our WRS extension, lowering the variance of ReSTIR, particularly with difficult lighting arrangements. Further, our MIS-style estimator shows a significant improvement compared to ReSTIR. In problem domains where resampling produces a function value for integration, such as path tracing, this comes at no additional cost. Lastly however, optimal weights do not appear to be beneficial for our approach.
Predictable blur behaviour for the bilateral filter
Researching a method for linear behaviour between the blurriness and spatial filter size of the bilateral filter
Edge-aware Bilateral Filtering
Reducing across-edge blurring for the bilateral filter
On-Mesh Bilateral Filtering
Bridging the Gap Between Texture and Object Space