COMPOSITION
DESIGN
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VQGAN + CLIP AI made Music Video for the song Canvas by ResonateRead more: VQGAN + CLIP AI made Music Video for the song Canvas by Resonate” In this video, I utilized artificial intelligence to generate an animated music video for the song Canvas by Resonate. This tool allows anyone to generate beautiful images using only text as the input. My question was, what if I used song lyrics as input to the AI, can I make perfect music synchronized videos automatically with the push of a button? Let me know how you think the AI did in this visual interpretation of the song. After getting caught up in the excitement around DALL·E2 (latest and greatest AI system, it’s INSANE), I searched for any way I could use similar image generation for music synchronization. Since DALL·E2 is not available to the public yet, my search led me to VQGAN + CLIP (Vector Quantized Generative Adversarial Network and Contrastive Language–Image Pre-training), before settling more specifically on Disco Diffusion V5.2 Turbo. If you don’t know what any of these words or acronyms mean, don’t worry, I was just as confused when I first started learning about this technology. I believe we’re reaching a turning point where entire industries are about to shift in reaction to this new process (which is essentially magic!). DoodleChaos” 
COLOR
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Colormaxxing – What if I told you that rgb(255, 0, 0) is not actually the reddest red you can have in your browser?Read more: Colormaxxing – What if I told you that rgb(255, 0, 0) is not actually the reddest red you can have in your browser?https://karuna.dev/colormaxxing https://webkit.org/blog-files/color-gamut/comparison.html https://oklch.com/#70,0.1,197,100  
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Photography Basics : Spectral Sensitivity Estimation Without a CameraRead more: Photography Basics : Spectral Sensitivity Estimation Without a Camerahttps://color-lab-eilat.github.io/Spectral-sensitivity-estimation-web/ A number of problems in computer vision and related fields would be mitigated if camera spectral sensitivities were known. As consumer cameras are not designed for high-precision visual tasks, manufacturers do not disclose spectral sensitivities. Their estimation requires a costly optical setup, which triggered researchers to come up with numerous indirect methods that aim to lower cost and complexity by using color targets. However, the use of color targets gives rise to new complications that make the estimation more difficult, and consequently, there currently exists no simple, low-cost, robust go-to method for spectral sensitivity estimation that non-specialized research labs can adopt. Furthermore, even if not limited by hardware or cost, researchers frequently work with imagery from multiple cameras that they do not have in their possession. To provide a practical solution to this problem, we propose a framework for spectral sensitivity estimation that not only does not require any hardware (including a color target), but also does not require physical access to the camera itself. Similar to other work, we formulate an optimization problem that minimizes a two-term objective function: a camera-specific term from a system of equations, and a universal term that bounds the solution space. Different than other work, we utilize publicly available high-quality calibration data to construct both terms. We use the colorimetric mapping matrices provided by the Adobe DNG Converter to formulate the camera-specific system of equations, and constrain the solutions using an autoencoder trained on a database of ground-truth curves. On average, we achieve reconstruction errors as low as those that can arise due to manufacturing imperfections between two copies of the same camera. We provide predicted sensitivities for more than 1,000 cameras that the Adobe DNG Converter currently supports, and discuss which tasks can become trivial when camera responses are available.  
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About color: What is a LUTRead more: About color: What is a LUThttp://www.lightillusion.com/luts.html https://www.shutterstock.com/blog/how-use-luts-color-grading A LUT (Lookup Table) is essentially the modifier between two images, the original image and the displayed image, based on a mathematical formula. Basically conversion matrices of different complexities. There are different types of LUTS – viewing, transform, calibration, 1D and 3D. 
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mmColorTarget – Nuke Gizmo for color matching a MacBeth chartRead more: mmColorTarget – Nuke Gizmo for color matching a MacBeth charthttps://www.marcomeyer-vfx.de/posts/2014-04-11-mmcolortarget-nuke-gizmo/ https://www.marcomeyer-vfx.de/posts/mmcolortarget-nuke-gizmo/ https://vimeo.com/9.1652466e+07 https://www.nukepedia.com/gizmos/colour/mmcolortarget 
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Photography basics: Why Use a (MacBeth) Color Chart?Read more: Photography basics: Why Use a (MacBeth) Color Chart?Start here: https://www.pixelsham.com/2013/05/09/gretagmacbeth-color-checker-numeric-values/ https://www.studiobinder.com/blog/what-is-a-color-checker-tool/ In LightRoom in Final Cut in Nuke Note: In Foundry’s Nuke, the software will map 18% gray to whatever your center f/stop is set to in the viewer settings (f/8 by default… change that to EV by following the instructions below). 
 You can experiment with this by attaching an Exposure node to a Constant set to 0.18, setting your viewer read-out to Spotmeter, and adjusting the stops in the node up and down. You will see that a full stop up or down will give you the respective next value on the aperture scale (f8, f11, f16 etc.).One stop doubles or halves the amount or light that hits the filmback/ccd, so everything works in powers of 2. 
 So starting with 0.18 in your constant, you will see that raising it by a stop will give you .36 as a floating point number (in linear space), while your f/stop will be f/11 and so on.If you set your center stop to 0 (see below) you will get a relative readout in EVs, where EV 0 again equals 18% constant gray. In other words. Setting the center f-stop to 0 means that in a neutral plate, the middle gray in the macbeth chart will equal to exposure value 0. EV 0 corresponds to an exposure time of 1 sec and an aperture of f/1.0. This will set the sun usually around EV12-17 and the sky EV1-4 , depending on cloud coverage. To switch Foundry’s Nuke’s SpotMeter to return the EV of an image, click on the main viewport, and then press s, this opens the viewer’s properties. Now set the center f-stop to 0 in there. And the SpotMeter in the viewport will change from aperture and fstops to EV. 
LIGHTING
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Magnific.ai Relight – change the entire lighting of a sceneRead more: Magnific.ai Relight – change the entire lighting of a sceneIt’s a new Magnific spell that allows you to change the entire lighting of a scene and, optionally, the background with just: 1/ A prompt OR 
 2/ A reference image OR
 3/ A light map (drawing your own lights)https://x.com/javilopen/status/1805274155065176489 
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Vahan Sosoyan MakeHDR – an OpenFX open source plug-in for merging multiple LDR images into a single HDRIRead more: Vahan Sosoyan MakeHDR – an OpenFX open source plug-in for merging multiple LDR images into a single HDRIhttps://github.com/Sosoyan/make-hdr Feature notes- Merge up to 16 inputs with 8, 10 or 12 bit depth processing
- User friendly logarithmic Tone Mapping controls within the tool
- Advanced controls such as Sampling rate and Smoothness
 Available at cross platform on Linux, MacOS and Windows Works consistent in compositing applications like Nuke, Fusion, Natron. NOTE: The goal is to clean the initial individual brackets before or at merging time as much as possible. 
 This means:- keeping original shooting metadata
- de-fringing
- removing aberration (through camera lens data or automatically)
- at 32 bit
- in ACEScg (or ACES) wherever possible
  
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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. (more…)
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Unity 3D resourcesRead more: Unity 3D resources http://answers.unity3d.com/questions/12321/how-can-i-start-learning-unity-fast-list-of-tutori.html If you have no previous experience with Unity, start with these six video tutorials which give a quick overview of the Unity interface and some important features http://unity3d.com/support/documentation/video/ 
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How to Direct and Edit a Fight Scene for Rhythm and PacingRead more: How to Direct and Edit a Fight Scene for Rhythm and Pacingwww.premiumbeat.com/blog/directing-fight-scene-cinematography/ 1- Frame the action 2- Stage the action 3- Use camera movements 4- Set a rhythm 5- Control the speed of the action 
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What is physically correct lighting all about?Read more: What is physically correct lighting all about?http://gamedev.stackexchange.com/questions/60638/what-is-physically-correct-lighting-all-about 2012-08 Nathan Reed wrote: Physically-based shading means leaving behind phenomenological models, like the Phong shading model, which are simply built to “look good” subjectively without being based on physics in any real way, and moving to lighting and shading models that are derived from the laws of physics and/or from actual measurements of the real world, and rigorously obey physical constraints such as energy conservation. For example, in many older rendering systems, shading models included separate controls for specular highlights from point lights and reflection of the environment via a cubemap. You could create a shader with the specular and the reflection set to wildly different values, even though those are both instances of the same physical process. In addition, you could set the specular to any arbitrary brightness, even if it would cause the surface to reflect more energy than it actually received. In a physically-based system, both the point light specular and the environment reflection would be controlled by the same parameter, and the system would be set up to automatically adjust the brightness of both the specular and diffuse components to maintain overall energy conservation. Moreover you would want to set the specular brightness to a realistic value for the material you’re trying to simulate, based on measurements. Physically-based lighting or shading includes physically-based BRDFs, which are usually based on microfacet theory, and physically correct light transport, which is based on the rendering equation (although heavily approximated in the case of real-time games). It also includes the necessary changes in the art process to make use of these features. Switching to a physically-based system can cause some upsets for artists. First of all it requires full HDR lighting with a realistic level of brightness for light sources, the sky, etc. and this can take some getting used to for the lighting artists. It also requires texture/material artists to do some things differently (particularly for specular), and they can be frustrated by the apparent loss of control (e.g. locking together the specular highlight and environment reflection as mentioned above; artists will complain about this). They will need some time and guidance to adapt to the physically-based system. On the plus side, once artists have adapted and gained trust in the physically-based system, they usually end up liking it better, because there are fewer parameters overall (less work for them to tweak). Also, materials created in one lighting environment generally look fine in other lighting environments too. This is unlike more ad-hoc models, where a set of material parameters might look good during daytime, but it comes out ridiculously glowy at night, or something like that. Here are some resources to look at for physically-based lighting in games: SIGGRAPH 2013 Physically Based Shading Course, particularly the background talk by Naty Hoffman at the beginning. You can also check out the previous incarnations of this course for more resources. Sébastien Lagarde, Adopting a physically-based shading model and Feeding a physically-based shading model And of course, I would be remiss if I didn’t mention Physically-Based Rendering by Pharr and Humphreys, an amazing reference on this whole subject and well worth your time, although it focuses on offline rather than real-time rendering. 
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9 Best Hacks to Make a Cinematic Video with Any CameraRead more: 9 Best Hacks to Make a Cinematic Video with Any Camerahttps://www.flexclip.com/learn/cinematic-video.html - Frame Your Shots to Create Depth
- Create Shallow Depth of Field
- Avoid Shaky Footage and Use Flexible Camera Movements
- Properly Use Slow Motion
- Use Cinematic Lighting Techniques
- Apply Color Grading
- Use Cinematic Music and SFX
- Add Cinematic Fonts and Text Effects
- Create the Cinematic Bar at the Top and the Bottom
  
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