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Intel Open Image Denoise is an open source library of high-performance, high-quality denoising filters for images rendered with ray tracing. Intel Open Image Denoise is part of the Intel® oneAPI Rendering Toolkit and is released under the permissive Apache 2.0 license.
The purpose of Intel Open Image Denoise is to provide an open, high-quality, efficient, and easy-to-use denoising library that allows one to significantly reduce rendering times in ray tracing based rendering applications. It filters out the Monte Carlo noise inherent to stochastic ray tracing methods like path tracing, reducing the amount of necessary samples per pixel by even multiple orders of magnitude (depending on the desired closeness to the ground truth). A simple but flexible C/C++ API ensures that the library can be easily integrated into most existing or new rendering solutions.
At the heart of the Intel Open Image Denoise library is a collection of efficient deep learning based denoising filters, which were trained to handle a wide range of samples per pixel (spp), from 1 spp to almost fully converged. Thus it is suitable for both preview and final-frame rendering. The filters can denoise images either using only the noisy color (beauty) buffer, or, to preserve as much detail as possible, can optionally utilize auxiliary feature buffers as well (e.g. albedo, normal). Such buffers are supported by most renderers as arbitrary output variables (AOVs) or can be usually implemented with little effort.
https://www.cbc.ca/listen/live-radio/1-50-q/clip/16014382-tom-hanks
Two-time Oscar winner Tom Hanks (Forrest Gump, Philadelphia, A League of Their Own) on his debut novel “The Making of Another Major Motion Picture Masterpiece,” the insecurities he’s felt throughout his career, and what drives his passion for filmmaking when it feels like “the odds are stacked against you.”
Nothing comes easy if you learnt all through mistakes…
The change will happen sometime next year and will charge some users on a per-seat model, similar to Photoshop pricing.
Game developers using Unreal Engine won’t be affected and will continue to pay for a license based on a royalty model. However, users in industries like film or automotive will be moved to per-seat pricing, meaning they’ll be charged for the subscription the same way someone might pay for Photoshop.
https://www.theverge.com/2023/10/5/23905082/epic-unreal-engine-pricing-change-film-automotive
https://neuralradiancefields.io/luma-interactive-scenes-announced/
“…these are in fact Gaussian Splats that are being run and it’s a proprietary iteration of the original Inria paper. They hybridize the performance gain of realtime rendering with Gaussian Splatting with robust cloud based rendering that’s already widely being used in commercial applications. This has been in the works for a while over at Luma and I had the opportunity to try out some of my datasets on their new method.”
MICHAEL RUBLOFF
https://www.roadtovr.com/meta-quest-3-oculus-preview-connect-2023/
https://huggingface.co/spaces/jbilcke-hf/ai-comic-factory
this is the epic story of a group of talented digital artists trying to overcame daily technical challenges to achieve incredibly photorealistic projects of monsters and aliens
https://www.blackmagicdesign.com/ca/products/blackmagiccamera
You can adjust settings such as frame rate, shutter angle, white balance and ISO all in a single tap. Or, record directly to Blackmagic Cloud in industry standard 10-bit Apple ProRes files up to 4K! Recording to Blackmagic Cloud Storage lets you collaborate on DaVinci Resolve projects with editors anywhere in the world, all at the same time!
https://www.reshot.ai/3d-gaussian-splatting
what are 3D Gaussians? They are a generalization of 1D Gaussians (the bell curve) to 3D. Essentially they are ellipsoids in 3D space, with a center, a scale, a rotation, and “softened edges”.
Each 3D Gaussian is optimized along with a (viewdependant) color and opacity. When blended together, here’s the visualization of the full model, rendered from ANY angle. As you can see, 3D Gaussian Splatting captures extremely well the fuzzy and soft nature of the plush toy, something that photogrammetry-based methods struggle to do.
https://gilwizen.com/laowa-25mm-ultra-macro-lens-review/
https://www.cameralabs.com/laowa-25mm-f2-8-2-5-5x-ultra-macro-review/
Combining a Laowa 25mm 2.5x lens with a Kenko 12mm extension tube
To find the combined magnification when using a Laowa 25mm 2.5x lens with a 12mm Kenko extension tube, given the magnification of the lens itself, the extension tube length, and the combined setup, you can calculate the total magnification.
First, consider the magnification of the lens itself, which is 2.5x.
Then, to find the total magnification when the extension tube is attached, you can use the formula:
Total Magnification = Magnification of the Lens + (Magnification of the Lens * Extension Tube Length / Focal Length of the Lens)
In this case, the extension tube length is 12mm, and the focal length of the lens is 25mm. Using the values:
Total Magnification with 2.5x = 2.5 + (2.5 * 12 / 25) = 2.5 + (30 / 25) = 2.5 + 1.2 = 3.7x
Total Magnification with 5x = 5 + (5 * 12 / 25) = 5 + (60 / 25) = 5 + 2.4 = 7.4x
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