COMPOSITION
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Composition and The Expressive Nature Of LightRead more: Composition and The Expressive Nature Of Lighthttp://www.huffingtonpost.com/bill-danskin/post_12457_b_10777222.html George Sand once said “ The artist vocation is to send light into the human heart.” 
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Composition – These are the basic lighting techniques you need to know for photography and filmRead more: Composition – These are the basic lighting techniques you need to know for photography and filmhttp://www.diyphotography.net/basic-lighting-techniques-need-know-photography-film/ Amongst the basic techniques, there’s… 1- Side lighting – Literally how it sounds, lighting a subject from the side when they’re faced toward you 2- Rembrandt lighting – Here the light is at around 45 degrees over from the front of the subject, raised and pointing down at 45 degrees 3- Back lighting – Again, how it sounds, lighting a subject from behind. This can help to add drama with silouettes 4- Rim lighting – This produces a light glowing outline around your subject 5- Key light – The main light source, and it’s not necessarily always the brightest light source 6- Fill light – This is used to fill in the shadows and provide detail that would otherwise be blackness 7- Cross lighting – Using two lights placed opposite from each other to light two subjects 
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Cinematographers Blueprint 300dpi posterRead more: Cinematographers Blueprint 300dpi posterThe 300dpi digital poster is now available to all PixelSham.com subscribers. If you have already subscribed and wish a copy, please send me a note through the contact page. 
DESIGN
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The illusion of sex 2009Read more: The illusion of sex 2009 Richard Russell Harvard University, USA In the Illusion of Sex, two faces are perceived as male and female. However, both faces are actually versions of the same androgynous face. One face was created by increasing the contrast of the androgynous face, while the other face was created by decreasing the contrast. The face with more contrast is perceived as female, while the face with less contrast is perceived as male. The Illusion of Sex demonstrates that contrast is an important cue for perceiving the sex of a face, with greater contrast appearing feminine, and lesser contrast appearing masculine. Russell, R. (2009) A sex difference in facial pigmentation and its exaggeration by cosmetics. Perception, (38)1211-1219. 
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boldtron – 𝗗𝗘𝗣𝗜𝗖𝗧𝗜𝗡𝗚 𝗪𝗔𝗧𝗘𝗥𝗚𝗨𝗡𝗦Read more: boldtron – 𝗗𝗘𝗣𝗜𝗖𝗧𝗜𝗡𝗚 𝗪𝗔𝗧𝗘𝗥𝗚𝗨𝗡𝗦See this Instagram post by @boldtron using ComfyUI + Krea https://www.instagram.com/p/C5v-H0PNYYg/?utm_source=ig_web_button_share_sheet 
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This legendary DC Comics style guide was nearly lost for years – now you can buy itRead more: This legendary DC Comics style guide was nearly lost for years – now you can buy ithttps://www.fastcompany.com/91133306/dc-comics-style-guide-was-lost-for-years-now-you-can-buy-it Reproduced from a rare original copy, the book features over 165 highly-detailed scans of the legendary art by José Luis García-López, with an introduction by Paul Levitz, former president of DC Comics. https://standardsmanual.com/products/1982-dc-comics-style-guide 
COLOR
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Yasuharu YOSHIZAWA – Comparison of sRGB vs ACREScg in NukeRead 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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“Reality” is constructed by your brain. Here’s what that means, and why it matters.Read more: “Reality” is constructed by your brain. Here’s what that means, and why it matters.“Fix your gaze on the black dot on the left side of this image. But wait! Finish reading this paragraph first. As you gaze at the left dot, try to answer this question: In what direction is the object on the right moving? Is it drifting diagonally, or is it moving up and down?”  What color are these strawberries?  Are A and B the same gray?  
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The Color of Infinite TemperatureRead more: The Color of Infinite TemperatureThis is the color of something infinitely hot.  Of course you’d instantly be fried by gamma rays of arbitrarily high frequency, but this would be its spectrum in the visible range. johncarlosbaez.wordpress.com/2022/01/16/the-color-of-infinite-temperature/ This is also the color of a typical neutron star. They’re so hot they look the same. 
 It’s also the color of the early Universe!This was worked out by David Madore.  The color he got is sRGB(148,177,255). 
 www.htmlcsscolor.com/hex/94B1FFAnd according to the experts who sip latte all day and make up names for colors, this color is called ‘Perano’. 
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Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color pickingRead more: Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color pickinghttps://bottosson.github.io/misc/colorpicker https://bottosson.github.io/posts/colorpicker/ https://www.smashingmagazine.com/2024/10/interview-bjorn-ottosson-creator-oklab-color-space/ One problem with sRGB is that in a gradient between blue and white, it becomes a bit purple in the middle of the transition. That’s because sRGB really isn’t created to mimic how the eye sees colors; rather, it is based on how CRT monitors work. That means it works with certain frequencies of red, green, and blue, and also the non-linear coding called gamma. It’s a miracle it works as well as it does, but it’s not connected to color perception. When using those tools, you sometimes get surprising results, like purple in the gradient. There were also attempts to create simple models matching human perception based on XYZ, but as it turned out, it’s not possible to model all color vision that way. Perception of color is incredibly complex and depends, among other things, on whether it is dark or light in the room and the background color it is against. When you look at a photograph, it also depends on what you think the color of the light source is. The dress is a typical example of color vision being very context-dependent. It is almost impossible to model this perfectly. I based Oklab on two other color spaces, CIECAM16 and IPT. I used the lightness and saturation prediction from CIECAM16, which is a color appearance model, as a target. I actually wanted to use the datasets used to create CIECAM16, but I couldn’t find them. IPT was designed to have better hue uniformity. In experiments, they asked people to match light and dark colors, saturated and unsaturated colors, which resulted in a dataset for which colors, subjectively, have the same hue. IPT has a few other issues but is the basis for hue in Oklab. In the Munsell color system, colors are described with three parameters, designed to match the perceived appearance of colors: Hue, Chroma and Value. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. Modern color spaces and models, such as CIELAB, Cam16 and Björn Ottosson own Oklab, are very similar in their construction.  By far the most used color spaces today for color picking are HSL and HSV, two representations introduced in the classic 1978 paper “Color Spaces for Computer Graphics”. HSL and HSV designed to roughly correlate with perceptual color properties while being very simple and cheap to compute. Today HSL and HSV are most commonly used together with the sRGB color space.  One of the main advantages of HSL and HSV over the different Lab color spaces is that they map the sRGB gamut to a cylinder. This makes them easy to use since all parameters can be changed independently, without the risk of creating colors outside of the target gamut.  The main drawback on the other hand is that their properties don’t match human perception particularly well. 
 Reconciling these conflicting goals perfectly isn’t possible, but given that HSV and HSL don’t use anything derived from experiments relating to human perception, creating something that makes a better tradeoff does not seem unreasonable. With this new lightness estimate, we are ready to look into the construction of Okhsv and Okhsl.  
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FXGuide – ACES 2.0 with ILM’s Alex FryRead more: FXGuide – ACES 2.0 with ILM’s Alex Fryhttps://draftdocs.acescentral.com/background/whats-new/ ACES 2.0 is the second major release of the components that make up the ACES system. The most significant change is a new suite of rendering transforms whose design was informed by collected feedback and requests from users of ACES 1. The changes aim to improve the appearance of perceived artifacts and to complete previously unfinished components of the system, resulting in a more complete, robust, and consistent product. Highlights of the key changes in ACES 2.0 are as follows: - New output transforms, including:
- A less aggressive tone scale
- More intuitive controls to create custom outputs to non-standard displays
- Robust gamut mapping to improve perceptual uniformity
- Improved performance of the inverse transforms
 
- Enhanced AMF specification
- An updated specification for ACES Transform IDs
- OpenEXR compression recommendations
- Enhanced tools for generating Input Transforms and recommended procedures for characterizing prosumer cameras
- Look Transform Library
- Expanded documentation
 Rendering TransformThe most substantial change in ACES 2.0 is a complete redesign of the rendering transform. ACES 2.0 was built as a unified system, rather than through piecemeal additions. Different deliverable outputs “match” better and making outputs to display setups other than the provided presets is intended to be user-driven. The rendering transforms are less likely to produce undesirable artifacts “out of the box”, which means less time can be spent fixing problematic images and more time making pictures look the way you want. Key design goals- Improve consistency of tone scale and provide an easy to use parameter to allow for outputs between preset dynamic ranges
- Minimize hue skews across exposure range in a region of same hue
- Unify for structural consistency across transform type
- Easy to use parameters to create outputs other than the presets
- Robust gamut mapping to improve harsh clipping artifacts
- Fill extents of output code value cube (where appropriate and expected)
- Invertible – not necessarily reversible, but Output > ACES > Output round-trip should be possible
- Accomplish all of the above while maintaining an acceptable “out-of-the box” rendering
 
- New output transforms, including:
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No one could see the colour blue until modern timesRead more: No one could see the colour blue until modern timeshttps://www.businessinsider.com/what-is-blue-and-how-do-we-see-color-2015-2  The way humans see the world… until we have a way to describe something, even something so fundamental as a colour, we may not even notice that something it’s there. Ancient languages didn’t have a word for blue — not Greek, not Chinese, not Japanese, not Hebrew, not Icelandic cultures. And without a word for the colour, there’s evidence that they may not have seen it at all. 
 https://www.wnycstudios.org/story/211119-colorsEvery language first had a word for black and for white, or dark and light. The next word for a colour to come into existence — in every language studied around the world — was red, the colour of blood and wine. 
 After red, historically, yellow appears, and later, green (though in a couple of languages, yellow and green switch places). The last of these colours to appear in every language is blue.The only ancient culture to develop a word for blue was the Egyptians — and as it happens, they were also the only culture that had a way to produce a blue dye. 
 https://mymodernmet.com/shades-of-blue-color-history/True blue hues are rare in the natural world because synthesizing pigments that absorb longer-wavelength light (reds and yellows) while reflecting shorter-wavelength blue light requires exceptionally elaborate molecular structures—biochemical feats that most plants and animals simply don’t undertake. When you gaze at a blueberry’s deep blue surface, you’re actually seeing structural coloration rather than a true blue pigment. A fine, waxy bloom on the berry’s skin contains nanostructures that preferentially scatter blue and violet light, giving the fruit its signature blue sheen even though its inherent pigment is reddish. Similarly, many of nature’s most striking blues—like those of blue jays and morpho butterflies—arise not from blue pigments but from microscopic architectures in feathers or wing scales. These tiny ridges and air pockets manipulate incoming light so that blue wavelengths emerge most prominently, creating vivid, angle-dependent colors through scattering rather than pigment alone. (more…)
LIGHTING
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Photography basics: Lumens vs Candelas (candle) vs Lux vs FootCandle vs Watts vs Irradiance vs IlluminanceRead more: Photography basics: Lumens vs Candelas (candle) vs Lux vs FootCandle vs Watts vs Irradiance vs Illuminancehttps://www.translatorscafe.com/unit-converter/en-US/illumination/1-11/ The power output of a light source is measured using the unit of watts W. This is a direct measure to calculate how much power the light is going to drain from your socket and it is not relatable to the light brightness itself. The amount of energy emitted from it per second. That energy comes out in a form of photons which we can crudely represent with rays of light coming out of the source. The higher the power the more rays emitted from the source in a unit of time. Not all energy emitted is visible to the human eye, so we often rely on photometric measurements, which takes in account the sensitivity of human eye to different wavelenghts Details in the post 
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Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering and Denoising for HDR View SynthesisRead more: Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering and Denoising for HDR View Synthesishttps://srameo.github.io/projects/le3d/ LE3D is a method for real-time HDR view synthesis from RAW images. It is particularly effective for nighttime scenes. https://github.com/Srameo/LE3D 
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NVidia DiffusionRenderer – Neural Inverse and Forward Rendering with Video Diffusion Models. How NVIDIA reimagined relightingRead more: NVidia DiffusionRenderer – Neural Inverse and Forward Rendering with Video Diffusion Models. How NVIDIA reimagined relightinghttps://www.fxguide.com/quicktakes/diffusing-reality-how-nvidia-reimagined-relighting/ https://research.nvidia.com/labs/toronto-ai/DiffusionRenderer/ 
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