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Neural network algorithm for solving ray-tracing problem

    https://ieeexplore.ieee.org/document/1201979/
    This work is dedicated to the study of neural network method for solving of ray-tracing task, which appears in 3D visualization algorithms. Physical representation of the task is the problem of finding the nearest point of the "vision" ray crossing with the surfaces of the scene. Application: Real time 3D visualization, rendering of the complex scenes, containing …

Neural Ray-Tracing: Learning Surfaces and Reflectance …

    https://arxiv.org/abs/2104.13562
    Neural Ray-Tracing: Learning Surfaces and Reflectance for Relighting and View Synthesis Julian Knodt, Joe Bartusek, Seung-Hwan Baek, Felix Heide Recent neural rendering methods have demonstrated accurate view interpolation by predicting volumetric density and color with a neural network.

Take a Deep Dive into Ray Tracing, Machine Learning and …

    https://developer.nvidia.com/blog/take-a-deep-dive-into-ray-tracing-machine-learning-and-neural-networks-through-siggraph-frontiers/
    Starting on May 24, you can take part in industry-leading discussions around ray tracing, machine learning and neural networks. These pre-conference webinars are ongoing educational events that will take place through June 18, and feature several …

GitHub - princeton-computational …

    https://github.com/princeton-computational-imaging/neural_raytracing
    Neural Ray-tracing is an extension on top of NeRF & VolSDF to allow for efficient ray-marching, so that dynamic lighting conditions can be rendered. This is done by adding an additional network that accounts for lighting based on position and viewing direction, as well as learning correct surfaces such that an SDF can be quickly raymarched.

Points-connecting neural network ray tracing - PubMed

    https://pubmed.ncbi.nlm.nih.gov/34469953/
    Unsupervised neural network ray tracing (NNRT) to calculate a light ray path connecting given points in a gradient-index medium is proposed here. If two points are given, the NNRT can provide a light ray path passing through these points without knowledge of the light ray direction. Maxwell's fishey …

End-to-end sensor and neural network design using …

    https://pubmed.ncbi.nlm.nih.gov/34809257/
    The proposed ray tracing model makes no thin lens nor paraxial approximation, and is valid for any field of view and point source position. Using the gradient backpropagation framework for neural network optimization, any of the lens parameter can then be jointly optimized along with the neural network parameters.

NVIDIA RTX Ray Tracing | NVIDIA Developer

    https://developer.nvidia.com/rtx/ray-tracing
    A real-time ray-tracing SDK, RTXDI offers photorealistic lighting of night and indoor scenes that require computing shadows from 100,000s to millions of area lights. No more baking, no more hero lights. Unlock unrestrained creativity even with limited ray-per-pixel counts.

Pdf light ray tracing and neural networks - Canadian instructions ...

    https://eyedolizelashandbrow.net/2022/pdf-light-ray-tracing-and-neural-networks/
    Ray tracing is a method of calculating the path of light through a light pipe through a virtual model Lumex uses state-of-the-a rt ray trace software with precise 3D CAD/CAM models for optimal light transmittance to ensure proper light pipe design. Physically Based Ray Tracing (PBRT) software packaged in a platform-independent Docker container.

NVIDIA Brings AI to Ray Tracing to Speed Graphics Workloads

    https://blogs.nvidia.com/blog/2017/05/10/ai-for-ray-tracing/
    (Ray tracing is a technique that uses complex math to realistically simulate how light interacts with surfaces in a specific space .) The ray tracing process generates highly realistic imagery but is computationally intensive, and can leave a …

Lecture 16: Optimizing Ray Tracing (Part II)

    https://gfxcourses.stanford.edu/cs348k/spring21content/media/rtoptimization2/16_rtoptimization2.pdf
    Input to network is noisy RGB image * + additional normal, depth, and roughness channels ... Then decode with neural decoder (“reconstruction”) [Xiao 20] Stanford CS348K, Spring 2021 ... -More rays = can amortize costs of BVH build across many ray …

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