COMPOSITION
DESIGN
COLOR
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What is a Gamut or Color Space and why do I need to know about CIE
Read more: What is a Gamut or Color Space and why do I need to know about CIE

http://www.xdcam-user.com/2014/05/what-is-a-gamut-or-color-space-and-why-do-i-need-to-know-about-it/
In video terms gamut is normally related to as the full range of colours and brightness that can be either captured or displayed.
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Yasuharu YOSHIZAWA – Comparison of sRGB vs ACREScg in Nuke
Read more: Yasuharu YOSHIZAWA – Comparison of sRGB vs ACREScg in NukeAnswering the question that is often asked, “Do I need to use ACEScg to display an sRGB monitor in the end?” (Demonstration shown at an in-house seminar)
Comparison of scanlineRender output with extreme color lights on color charts with sRGB/ACREScg in color – OCIO -working space in NukeDownload the Nuke script:
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Rec-2020 – TVs new color gamut standard used by Dolby Vision?
Read more: Rec-2020 – TVs new color gamut standard used by Dolby Vision?https://www.hdrsoft.com/resources/dri.html#bit-depth

The dynamic range is a ratio between the maximum and minimum values of a physical measurement. Its definition depends on what the dynamic range refers to.
For a scene: Dynamic range is the ratio between the brightest and darkest parts of the scene.
For a camera: Dynamic range is the ratio of saturation to noise. More specifically, the ratio of the intensity that just saturates the camera to the intensity that just lifts the camera response one standard deviation above camera noise.
For a display: Dynamic range is the ratio between the maximum and minimum intensities emitted from the screen.
The Dynamic Range of real-world scenes can be quite high — ratios of 100,000:1 are common in the natural world. An HDR (High Dynamic Range) image stores pixel values that span the whole tonal range of real-world scenes. Therefore, an HDR image is encoded in a format that allows the largest range of values, e.g. floating-point values stored with 32 bits per color channel. Another characteristics of an HDR image is that it stores linear values. This means that the value of a pixel from an HDR image is proportional to the amount of light measured by the camera.
For TVs HDR is great, but it’s not the only new TV feature worth discussing.
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What causes color
Read more: What causes colorwww.webexhibits.org/causesofcolor/5.html
Water itself has an intrinsic blue color that is a result of its molecular structure and its behavior.

 
LIGHTING
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Neural Microfacet Fields for Inverse Rendering
Read more: Neural Microfacet Fields for Inverse Renderinghttps://half-potato.gitlab.io/posts/nmf/
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Fast, optimized ‘for’ pixel loops with OpenCV and Python to create tone mapped HDR images
Read more: Fast, optimized ‘for’ pixel loops with OpenCV and Python to create tone mapped HDR imageshttps://pyimagesearch.com/2017/08/28/fast-optimized-for-pixel-loops-with-opencv-and-python/
https://learnopencv.com/exposure-fusion-using-opencv-cpp-python/
Exposure Fusion is a method for combining images taken with different exposure settings into one image that looks like a tone mapped High Dynamic Range (HDR) image.
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Photography basics: Color Temperature and White Balance
Read more: Photography basics: Color Temperature and White BalanceColor Temperature of a light source describes the spectrum of light which is radiated from a theoretical “blackbody” (an ideal physical body that absorbs all radiation and incident light – neither reflecting it nor allowing it to pass through) with a given surface temperature.
https://en.wikipedia.org/wiki/Color_temperature
Or. Most simply it is a method of describing the color characteristics of light through a numerical value that corresponds to the color emitted by a light source, measured in degrees of Kelvin (K) on a scale from 1,000 to 10,000.
More accurately. The color temperature of a light source is the temperature of an ideal backbody that radiates light of comparable hue to that of the light source.
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Insta360-Research-Team DiT360 – High-Fidelity Panoramic Image Generation via Hybrid Training
Read more: Insta360-Research-Team DiT360 – High-Fidelity Panoramic Image Generation via Hybrid Traininghttps://github.com/Insta360-Research-Team/DiT360
DiT360 is a framework for high-quality panoramic image generation, leveraging both perspective and panoramic data in a hybrid training scheme. It adopts a two-level strategy—image-level cross-domain guidance and token-level hybrid supervision—to enhance perceptual realism and geometric fidelity.

 
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Alejandro Villabón and Rafał Kaniewski – Recover Highlights With 8-Bit to High Dynamic Range Half Float Copycat – Nuke
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Key/Fill ratios and scene composition using false colors and Nuke node
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The Perils of Technical Debt – Understanding Its Impact on Security, Usability, and Stability
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HoloCine – Holistic Generation of Cinematic Multi-Shot Long Video Narratives
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MiniMax-Remover – Taming Bad Noise Helps Video Object Removal Rotoscoping
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Types of Film Lights and their efficiency – CRI, Color Temperature and Luminous Efficacy
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Principles of Animation with Alan Becker, Dermot OConnor and Shaun Keenan
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Methods for creating motion blur in Stop motion
 
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