Our wiki is a comprehensive encyclopedia of online and offline aesthetics! We are a community dedicated to the identification, observation, and documentation of visual schemata.
What is an aesthetic? Why does everyone always argue about what aesthetics should be on this wiki?
The short answer: A collection of visual schema that creates a "mood."
Some types of aesthetics include:
Aesthetics originated from Internet communities (Ex: Cottagecore, Dark Academia)
National cultures (Americana, Traditional Polish) Note: Most articles that try to describe a national culture will be deleted. These articles should have a higher quality and risk stereotyping a nation.
Genres of fiction with established visual tropes (Ex: Cyberpunk, Gothic)
Holidays with iconic imagery and colors (Ex: Christmas, Halloween)
Locations that have expected activities, components, and types of people (Ex: Fanfare, Urbancore)
Music genres with consistent visual motifs present in cover art, music videos, etc (Ex: City Pop, Emo)
This does not mean all music genres should be present. For example, Pop and Alternative bands' do not have shared visual traits.
Periods of history with distinct visuals (Ex: Victorian, Y2K)
Stereotypes (Ex: Brocore, VSCO)
Subcultures that share music genres and fashion styles (Ex: Raver, Skinheads)
The long answer:
The word "aesthetic" originated as the philosophical discussion about what beauty is, how we should approach it, and why it exists. However, Millennials and Generation Z started using that term as an adjective that describes what they personally consider beautiful. For example: "After Denise finished watching The Virgin Suicides, she said, 'Wow. That was so aesthetic.'"
Aesthetics have now come to mean a collection of images, colors, objects, music, and writings that creates a specific emotion, purpose, and community. It is largely dependent on personal taste, cultural background, and exposure to different pieces of media. This definition is not official and can be debated. There is currently no dictionary definition that captures the complexity of this phenomenon, which arose in the Internet youth. Rather, people who participate in the community "know it when they see it." These elements are constantly debated, as the opinion on whether or not some aesthetics exist or are valid is constantly debated. This is especially true since everyone's own personal life factors into their opinions.
Here is an example of a debate that is going on within the community. Whether or not Lolita is an aesthetic varies on what counts as visual elements. On one hand, lace, petticoats, and bows are valid elements of visual schema. Those elements combine to spark feelings of kawaii, de-sexualization, rebellion, and appreciation of antique. On the other hand, aesthetics are made up of elements other than fashion, such as home decor or music. Fashion is the visual element, rather than the components making up the coord/outfit. That element is part of broader schemas such as Goth and Victorian. What counts as an element and what qualifies as sparking an emotion is a complicated subject.
So right now, the subject is trying to be defined by the community. What either fits into a larger schema or is distinct enough to warrant its own aesthetic is difficult to say and would depend on who you are asking.
Clip retrieval works by converting the text query to a CLIP embedding , then using that embedding to query a knn index of clip image embedddings
“Although our study doesn’t present ways to mitigate negative hunger-induced emotions, research suggests that being able to label an emotion can help people to regulate it, such as by recognising that we feel angry simply because we are hungry. Therefore, greater awareness of being ‘hangry’ could reduce the likelihood that hunger results in negative emotions and behaviours in individuals.”
A book of 1000 paintings and illustrations of robots created by artificial intelligence. The author generated all of the images in this book by writing original prompts for DALL·E 2, OpenAI’s AI system that can create realistic images and art from a description in natural language. Upon generating the images, the author curated and arranged the images to their own liking and takes ultimate responsibility for the content of this publication.
https://openai.com/dall-e-2/
https://github.com/CompVis/latent-diffusion
https://huggingface.co/spaces/multimodalart/latentdiffusion
https://mirror.xyz/0x0f6712c6ac4f02f47cA8b5cf200B224aE6fD8B69/AYLAsdtM090nHWpvWQ13exkaJoNyllkhxa9ffEUPOrg
Bitmap Image to 'Pixel Perfect' Vector Graphic or 3D model
The HTML5 application on this page converts your bitmap image online into a Scalable Vector Graphics or 3D model.
The result is 'pixel perfect'/lossless.
Rutt-Etra-Izer is a WebGL emulation of the classic Rutt-Etra video synthesizer. This demo replicates the Z-displacement, scanned-line look of the original, but does not attempt to replicate it’s full feature set.
The demo allows you to drag and drop your own images, manipulate them and save the output. Images are generated by scanning the pixels of the input image from top to bottom, with scan-line separated by the ‘Line Separation’ amount. For each line generated, the z-position of the vertices is dependent on the brightness of the pixels.
20 alternative interfaces for creating and editing images and text
https://github.com/constraint-systems
Flow
An experimental image editor that lets you set and direct pixel-flows.
Fracture
Shatter and recombine images using a grid of viewports.
Tri
Tri is an experimental image distorter. You can choose an image to render using a WebGL quad, adjust the texture and position coordinates to create different distortions, and save the result.
Tile
Layout images using a tiling tree layout. Move, split, and resize images using keyboard controls.
Sift
Slice an image into multiple layers. You can offset the slices to create interference patterns and pseudo-3D effects.
Automadraw
Draw and evolve your drawing using cellular automata on a pixel grid with two keyboard-controlled cursors.
Span
Lay out and rearrange text, line by line, using keyboard controls.
Stamp
Image-paint from a source image palette using keyboard controls.
Collapse
Collapse an image into itself using ranked superpixels.
Res
Selectively pixelate an image using a compression algorithm.
Rgb
Pixel-paint using keyboard controls.
Face
Edit both the text and the font it is rendered in.
Pal
Apply an eight-color terminal color scheme to an image. Use the keyboard controls to choose a theme, set thresholds, and cycle hues.
Bix
Draw on binary to glitch text.
Diptych
Pixel-reflow an image to match the dimensions of your text. Save the result as a diptych.
Slide
Divide and slide-stretch an image using keyboard controls.
Freeconfig
Push around image pixels in blocks.
Moire
Generate angular skyscapes using Asteroids-like ship controls.
Hex
A keyboard-driven, grid-based drawing tool.
Etch
A keyboard-based pixel drawing tool.
About
Constraint Systems is a collection of experimental web-based creative tools. They are an ongoing attempt to explore alternative ways of interacting with pixels and text on a computer screen. I hope to someday build these ideas into something larger, but the plan for now is to keep the scopes small and the releases quick.
Can I use the art I find here? How should I credit the artist?
Yes, you can use any of the art submitted to this site. Even in commercial projects. Just be sure to adhere to the license terms. Artists often indicate how they would like to be credited in the "Copyright/Attribution Notice:" section of the submission. You can find this between the submission's description and the list of downloadable files. If no Copyright/Attribution Notice instructions are given, a good way to credit an author for any asset is to put the following text in your game's credits file and on your game's credits screen:
"[asset name]" by [author name] licensed [license(s)]: [asset url]
For example:
"Whispers of Avalon: Grassland Tileset" by Leonard Pabin licensed CC-BY 3.0, GPL 2.0, or GPL 3.0: https://opengameart.org/node/3009
OpenGameArt Search + Reverse Image Search
Hint: Start search term with http(s):// for reverse image search.
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Neural Cellular Automata (NCA We use NCA to refer to both Neural Cellular Automata and Neural Cellular Automaton.) are capable of learning a diverse set of behaviours: from generating stable, regenerating, static images , to segmenting images , to learning to “self-classify” shapes . The inductive bias imposed by using cellular automata is powerful. A system of individual agents running the same learned local rule can solve surprisingly complex tasks. Moreover, individual agents, or cells, can learn to coordinate their behavior even when separated by large distances. By construction, they solve these tasks in a massively parallel and inherently degenerate Degenerate in this case refers to the biological concept of degeneracy. way. Each cell must be able to take on the role of any other cell - as a result they tend to generalize well to unseen situations.
In this work, we apply NCA to the task of texture synthesis. This task involves reproducing the general appearance of a texture template, as opposed to making pixel-perfect copies. We are going to focus on texture losses that allow for a degree of ambiguity. After training NCA models to reproduce textures, we subsequently investigate their learned behaviors and observe a few surprising effects. Starting from these investigations, we make the case that the cells learn distributed, local, algorithms.
To do this, we apply an old trick: we employ neural cellular automata as a differentiable image parameterization .
Welcome to Smithsonian Open Access, where you can download, share, and reuse millions of the Smithsonian’s images—right now, without asking. With new platforms and tools, you have easier access to more than 3 million 2D and 3D digital items from our collections—with many more to come. This includes images and data from across the Smithsonian’s 19 museums, nine research centers, libraries, archives, and the National Zoo.
What will you create?
Download :https://github.com/Tw1ddle/geometrize/releases
Features
Recreate images as geometric primitives.
Start with hundreds of images with preset settings.
Export geometrized images to SVG, PNG, JPG, GIF and more.
Export geometrized images as HTML5 canvas or WebGL webpages.
Export shape data as JSON for use in custom projects and creations.
Control the algorithm at the core of Geometrize with ChaiScript scripts.
The papers summarized here are mainly from 2017 onwards.
Please refer to the Survey paper(Image Aesthetic Assessment:An Experimental Survey) before 2016.
Optical illusions don’t “trick the eye” nor “fool the brain”, nor reveal that “our brain sucks”, … but are fascinating!
They also teach us about our visual perception, and its limitations. My selection emphazises beauty and interactive experiments; I also attempt explanations of the underlying visual mechanisms where possible.
Returning visitor? Check →here for History/News
»Optical illusion« sounds derogative, as if exposing a malfunction of the visual system. Rather, I view these phenomena as highlighting particular good adaptations of our visual system to its experience with standard viewing situations. These experiences are based on normal visual conditions, and thus under unusual contexts can lead to inappropriate interpretations of a visual scene (=“Bayesian interpretation of perception”).
If you are not a vision scientist, you might find my explanations too highbrow. That is not on purpose, but vision research simply is not trivial, like any science. So, if an explanation seems gibberish, simply enjoy the phenomenon 😉.
A showcase with creative machine learning experiments
Web scraping describes techniques for automatically downloading and processing web content, or converting online text and other media into structured data that can then be used for various purposes. In short, the user writes a program to browse and analyze the web on their behalf, rather than doing so manually. This is a common practice in silicon valley, where open html pages are transformed into private property: Facebook began as a (horny) web scraping project, as did Google and all other search engines. Web scraping is also frequently used to acquire the massive datasets needed to train machine learning models, and has become an important research tool in fields such as journalism and sociology.
I define "scrapism" as the practice of web scraping for artistic, emotional, and critical ends. It combines aspects of data journalism, conceptual art, and hoarding, and offers a methodology to make sense of a world in which everything we do is mediated by internet companies. These companies surveill us, vacuum up every trace we leave behind, exploit our experiences and interject themselves into every possible moment. But in turn they also leave their own traces online, traces which when collected, filtered, and sorted can reveal (and possibly even alter) power relations. The premise of scrapism is that everything we need to know about power is online, hiding in plain sight.
This is a work-in-progress guide to web scraping as an artistic and critical practice, created by Sam Lavigne. I will be updating it over the coming months! I'll also be doing occasional live demos either on Twitch or YoutTube.
Shrub is a tool for painting-and-traveling, and even for painting while moving your own body (for example to use the color of your own pants).
If you touch with two fingers, you can immediately send your drawing as an SMS message. Shrub is designed as a mobile communication tool as much as a mobile drawing tool.
More pro tips: For the best drawings, pinch with your fingers to change the brush size. Twist with your fingers to change the brush softness. And of course, tap with one finger to show and hide the viewfinder.
The TX Modular System is open source audio-visual software for modular synthesis and video generation, built with SuperCollider (https://supercollider.github.io) and openFrameworks (https://openFrameworks.cc).
It can be used to build interactive audio-visual systems such as: digital musical instruments, interactive generative compositions with real-time visuals, sound design tools, & live audio-visual processing tools.
This version has been tested on MacOS (0.10.11) and Windows (10). The audio engine should also work on Linux.
The visual engine, TXV, has only been built so far for MacOS and Windows - it is untested on Linux.
The current TXV MacOS build will only work with Mojave (10.14) or earlier (10.11, 10.12 & 10.13) - but NOT Catalina (10.15) or later.
You don't need to know how to program to use this system. But if you can program in SuperCollider, some modules allow you to edit the SuperCollider code inside - to generate or process audio, add modulation, create animations, or run SuperCollider Patterns.
The new Collection online
From Dürer to the Rosetta Stone, explore 4.5 million objects.
The database is based on the British Museum's collection management tool, where we record what we know about our collection. It was created for the Museum to store information for its own use, and is therefore full of specialised terms, abbreviations and shorthand.
The Museum has been working on the database for more than 40 years and, even with more than two million records, we've only catalogued about half of the collection. We're adding and improving records every day but, even so, an object record may not have been checked. In many cases, the most recent research has not yet been added. There will be mistakes and omissions, but the Museum chooses to publish the data, rather than hold it until it is 'finished', as there will always be new information about an object. Only personal and sensitive information has been withheld.
No Home Like Place Airbnb is a global hotel filled with the same recurring items. Bed, chair, potted plant, all catered to our cosmopolitan sensibilities. We end up in a place that's completely interchangeable; a room is a room is a room. An algorithm finds these recurring items and replaces them with the same items from other listings.