{"id":26,"date":"2023-03-10T12:45:00","date_gmt":"2023-03-10T03:45:00","guid":{"rendered":"https:\/\/blog-en.flitto.com\/en\/company\/blog\/?p=26"},"modified":"2023-08-02T15:52:39","modified_gmt":"2023-08-02T06:52:39","slug":"why-do-ai-generated-hands-look-so-bad","status":"publish","type":"post","link":"https:\/\/datalab.flitto.com\/en\/company\/blog\/why-do-ai-generated-hands-look-so-bad\/","title":{"rendered":"Why do AI-generated hands look so bad?"},"content":{"rendered":"\n<p id=\"cbfa\">In more ways than one, artificial intelligence (AI) image generation technology continues to amuse and terrify people in and out of the industry.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:875\/1*FYZQTS1l2Xh5WcBs8ALqug.jpeg\" alt=\"\"\/><figcaption class=\"wp-element-caption\"><em>\u201cTh\u00e9\u00e2tre D\u2019op\u00e9ra Spatial\u201d by Jason Allen (Source: Colorado State Fair Fine Arts)<\/em><\/figcaption><\/figure>\n\n\n\n<p id=\"16bf\">The&nbsp;<a href=\"https:\/\/www.nytimes.com\/2022\/09\/02\/technology\/ai-artificial-intelligence-artists.html\" target=\"_blank\" rel=\"noreferrer noopener\">winning of an AI-generated art<\/a>&nbsp;at a fine arts competition has brought forth fierce conversation around the genre of digital art. <\/p>\n\n\n\n<p id=\"16bf\">The artist stood by the legitimacy of his win. He&nbsp;<a href=\"https:\/\/www.vice.com\/en\/article\/bvmvqm\/an-ai-generated-artwork-won-first-place-at-a-state-fair-fine-arts-competition-and-artists-are-pissed\" target=\"_blank\" rel=\"noreferrer noopener\">explained<\/a>&nbsp;that the quality of the final work had a lot to do with vigorous fine-tuning and prompt engineering as an artist; AI was just his choice of medium.<\/p>\n\n\n\n<p id=\"a590\">This event highlights the astonishing advancements of AI art. All it takes is some detailed prompts from skilled experts like the&nbsp;<a href=\"https:\/\/www.businessinsider.com\/prompt-engineering-ai-chatgpt-jobs-explained-2023-3\" target=\"_blank\" rel=\"noreferrer noopener\">emerging prompt engineers<\/a>&nbsp;and a bit of touch-up if necessary.<\/p>\n\n\n\n<p id=\"3b83\">In generating these works of robotic art, good prompts are crucial. <\/p>\n\n\n\n<p id=\"3b83\">It\u2019s rarely effective to use simple keywords as prompts. Long strings of keywords and specs, and highly specific phrases greatly assist the robot artist in generating the work accurately.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"33bd\">The effect and limitation of good prompts<\/h3>\n\n\n\n<p id=\"cadc\">Many advanced AI image generation models are publicly available.&nbsp;<\/p>\n\n\n\n<p id=\"cadc\">Midjourney is one such model; it has had&nbsp;<a href=\"https:\/\/tokenizedhq.com\/midjourney-statistics\/\" target=\"_blank\" rel=\"noreferrer noopener\">2.7 million members<\/a>&nbsp;using its Discord server as of 2022.<\/p>\n\n\n\n<p id=\"a226\">To visualize the effects and limitations of prompt refining in AI artworks, we will be using Midjourney as our main robot designer for today (unless explicitly credited otherwise).<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:709\/1*OYXTwvrKcKBDmx58yjjbtA.png\" alt=\"\"\/><figcaption class=\"wp-element-caption\"><em>Midjourney\u2019s work on \u201cgirl playing basketball\u201d<\/em><\/figcaption><\/figure>\n\n\n\n<p id=\"4d26\">The four images above have been generated based on a simple one-liner prompt: \u201cgirl playing basketball.\u201d <\/p>\n\n\n\n<p id=\"4d26\">They are not terrible, but there is a lot going on. <\/p>\n\n\n\n<p id=\"4d26\">The styles of the four images are inconsistent and broad. This makes them likely to miss the creative intentions of the user. <\/p>\n\n\n\n<p id=\"4d26\">This is where the necessity of detailed prompts enters the conversation.<\/p>\n\n\n\n<p id=\"0c11\">Next, we will try to apply some techniques used by prompt engineers to produce high-quality artworks. This technique involves writing prompts that can be better understood by machines. <\/p>\n\n\n\n<p id=\"0c11\">Usually, machine-friendly prompts involve multiple phrases clearly specifying numbers and specs required. This enables the AI engine to have a better chance of recalling the right set of images.<\/p>\n\n\n\n<p id=\"19c5\">To the prompt above, we added more details so that the bot could better understand what we expect it to create. <\/p>\n\n\n\n<p id=\"19c5\">The revised prompt is: \u201c<em>a smiling girl shooting a basketball at an outdoor basketball court. upper body shot with full arms. photorealistic. 8k high resolution. extremely detailed, no filter \u2014 ar 16:9<\/em>.\u201d<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:875\/1*2E4rrzD6BPKpAGtms4BAQA.png\" alt=\"\"\/><figcaption class=\"wp-element-caption\"><em>Image of \u201cgirl playing basketball,\u201d upgraded with better prompt<\/em><\/figcaption><\/figure>\n\n\n\n<p id=\"70b4\">We can see that the results have visibly become more specific. They are almost life-like like what we have asked (although imperfect. Note the complete absence of a basketball in the second image and the absence of a hand in the last image).<\/p>\n\n\n\n<p id=\"ab40\">However, it\u2019s important to note that detailed prompts in themselves do not guarantee foolproof results.<\/p>\n\n\n\n<p id=\"21a6\">Below, we have input a specific prompt: \u201c<em>renaissance-style art of a 17th century lady in a victorian dress elegantly holding a smartphone. ornate golden circular frame in the background. detailed, bright cinematic lighting, high resolution 8k \u2014 ar 3:2.<\/em>\u201d<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:875\/1*TATThhOpNtx69H0Y6jJuSQ.png\" alt=\"\"\/><\/figure>\n\n\n\n<p id=\"8fcd\">At a single glance, the images generated seem to correctly depict what the engine\u2019s been told to depict.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:228\/1*SefNi4EypfXYew35ZnTW3w.png\" alt=\"\"\/><\/figure>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:221\/1*rBlYmQ1_NYjktBgCAC2ULQ.png\" alt=\"\"\/><\/figure>\n\n\n\n<p id=\"9438\">Except for the hands.<\/p>\n\n\n\n<p id=\"39f7\">Even when producing results that generally adhere to the descriptions provided, AI engines still seem to have a hard time figuring out how human hands are supposed to look like.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"4574\">So what causes AI hands to look so bad?<\/h3>\n\n\n\n<p>The \u201chorrifying AI hands\u201d issue has been raised in&nbsp;<a href=\"https:\/\/petapixel.com\/2023\/03\/02\/why-ai-image-generators-cant-get-hands-right\/\" target=\"_blank\" rel=\"noreferrer noopener\">multiple<\/a>&nbsp;<a href=\"https:\/\/www.sciencefocus.com\/future-technology\/why-ai-generated-hands-are-the-stuff-of-nightmares-explained-by-a-scientist\/\" target=\"_blank\" rel=\"noreferrer noopener\">articles<\/a>&nbsp;and&nbsp;<a href=\"https:\/\/twitter.com\/mileszim\/status\/1613965684937224192?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E1613965684937224192%7Ctwgr%5Ee982cd409f71786d7ae9352bf900734401419b0c%7Ctwcon%5Es1_&amp;ref_url=https%3A%2F%2Fwww.buzzfeednews.com%2Farticle%2Fpranavdixit%2Fai-generated-art-hands-fingers-messed-up\" target=\"_blank\" rel=\"noreferrer noopener\">communities<\/a>. It is an ongoing struggle for many of the available models.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:709\/1*rlnqj2CkZt_V7kC-p2KksQ.png\" alt=\"\"\/><figcaption class=\"wp-element-caption\"><em>Detailed prompts when asked to do a \u201cshaka\u201d hand sign<\/em><\/figcaption><\/figure>\n\n\n\n<p id=\"43b1\">Some even&nbsp;<a href=\"https:\/\/bootcamp.uxdesign.cc\/how-to-draw-hands-with-an-ai-image-generator-776ce3a814fe\" target=\"_blank\" rel=\"noreferrer noopener\">suggest<\/a>&nbsp;that it would be the current best practice to avoid requiring visible hands in prompts for optimized AI art results (e.g., by using gloves).<\/p>\n\n\n\n<p id=\"43b1\">But what could be causing these anomalies in the first place? Flitto DataLab has sorted three possible reasons for it.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"1672\">One: The inherently challenging features of human hands<\/h4>\n\n\n\n<p id=\"f883\">Hands and feet are some of the most complex human body parts. A hand has 27 bones; a foot has 26. <\/p>\n\n\n\n<p id=\"f883\">Moreover, their unique structure lets the body part branch out and fold into several complex directions. It requires the artist to consider the unique perspective per each finger.<\/p>\n\n\n\n<p id=\"4abe\">In fact, the intricacies of the hands as a subject of art challenge many human artists in drawing them accurately, not only AI artists.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:875\/1*lKlVKizvEAZLogSK2xLgCA.png\" alt=\"\"\/><figcaption class=\"wp-element-caption\">Even hyperrealistic \u201cphotographs\u201d created with Midjourney are plagued with wrong amounts of fingers.<\/figcaption><\/figure>\n\n\n\n<p id=\"d03d\">However, AI models are able to emulate other intricate human features. So the \u201cinherent\u201d complexity of a certain body part can\u2019t be a sufficient excuse these impossible finger positions.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"1531\">Two: The limitations in AI image generation mechanism<\/h4>\n\n\n\n<p id=\"d62e\">Many of the AI image generation models utilize a \u201c<a href=\"https:\/\/www.washingtonpost.com\/technology\/interactive\/2022\/ai-image-generator\/\" target=\"_blank\" rel=\"noreferrer noopener\">diffusion model<\/a>\u201d to create images. <\/p>\n\n\n\n<p id=\"d62e\">In the diffusion model, the AI model is trained with a dataset of images labeled with texts. <\/p>\n\n\n\n<p id=\"d62e\">As the training process begins, the images are gradually cluttered with random pixels. Through this process, the AI model learns to recognize what the underlying image contains in spite of the layer of pixels that obscures the image.<\/p>\n\n\n\n<p id=\"d62e\">Next, the model is trained to \u201csubtract\u201d the added noises so that it can return clear images on its own. <\/p>\n\n\n\n<p id=\"d62e\">Once sufficient training is done, the AI model will have become capable of generating its own images out of pure noise that contains no information.<\/p>\n\n\n\n<p id=\"7bbb\">In other words, AI models are only able to produce&nbsp;<em>predictive<\/em>&nbsp;results based solely on the 2D images with which it has been trained. <\/p>\n\n\n\n<p id=\"7bbb\">This boils down to the model using probabilities to guess where the fingers could be located on a flat image,&nbsp;<a href=\"https:\/\/www.sciencefocus.com\/future-technology\/why-ai-generated-hands-are-the-stuff-of-nightmares-explained-by-a-scientist\/\" target=\"_blank\" rel=\"noreferrer noopener\">without actually understanding<\/a>&nbsp;the whole structure of a three-dimensional \u201chand.\u201d<\/p>\n\n\n\n<p id=\"47f2\">For the same reason, many AI models also have a difficult time producing the right amount of teeth or formulating letters and words into images. <\/p>\n\n\n\n<p id=\"47f2\">Many publicly available AI image models are also&nbsp;<a href=\"https:\/\/arxiv.org\/pdf\/2212.10562.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">character-blind<\/a>. They merely attempt to combine lines and curves into something that&nbsp;<em>look like<\/em>&nbsp;letters, not understanding what they are supposed to mean when put together.<\/p>\n\n\n\n<p id=\"f613\">For instance, below is the image to the prompt: \u201c<em>magazine cover that says \u2018<\/em><strong><em>BEWARE: DOG<\/em><\/strong><em>\u2019 with a photograph of a cool golden retriever with sunglasses at a pool party.<\/em>\u201d<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:709\/1*VAx9yvy7P8qD46DYm1so3g.png\" alt=\"\"\/><figcaption class=\"wp-element-caption\"><em>Example of gibberish text in AI-generated image<\/em><\/figcaption><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"0fac\">Three: Insufficient data on hand images<\/h4>\n\n\n\n<p id=\"2b6d\">The above examples contain results commonly expected in the more publicly released AI image generation models.<\/p>\n\n\n\n<p id=\"4489\">However, as&nbsp;<a href=\"https:\/\/arxiv.org\/pdf\/2212.10562.pdf\" rel=\"noreferrer noopener\" target=\"_blank\">Google researchers<\/a>&nbsp;and other&nbsp;<a href=\"https:\/\/www.buzzfeednews.com\/article\/pranavdixit\/ai-generated-art-hands-fingers-messed-up\" rel=\"noreferrer noopener\" target=\"_blank\">experts<\/a>&nbsp;see it, there exists a more concrete resolution to this phenomenon.<\/p>\n\n\n\n<p id=\"6d1b\">Google\u2019s Parti was able to partially address a similar issue by simply incorporating a larger number of parameters \u2014 up to&nbsp;<a href=\"https:\/\/parti.research.google\/\" target=\"_blank\" rel=\"noreferrer noopener\">a whopping 20 billion<\/a>. <\/p>\n\n\n\n<p id=\"6d1b\">Parti, one of the current state-of-the-art image generation engines, demonstrates an advanced capability to render symbols and texts.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:875\/1*CazOTPPc5RmLPDp7-G4_fA.png\" alt=\"\"\/><figcaption class=\"wp-element-caption\"><em>(Prompt: <\/em>\u201cA portrait photo of a kangaroo wearing an orange hoodie and blue sunglasses standing on the grass in front of the Sydney Opera House holding a sign on the chest that says&nbsp;<strong>Welcome Friends!<\/strong>\u201d<em>&nbsp;Source:&nbsp;<a href=\"https:\/\/parti.research.google\/\" target=\"_blank\" rel=\"noreferrer noopener\">Parti<\/a>)<\/em><\/figcaption><\/figure>\n\n\n\n<p id=\"03d8\">It can be observed that the number of parameters greatly affects the overall quality of the results, including the text.<\/p>\n\n\n\n<p id=\"48ef\">Under a similar mechanism, incorporating a more comprehensive dataset containing high-quality hand images could improve engine performance. <\/p>\n\n\n\n<p id=\"48ef\">A Stability AI spokesperson&nbsp;<a href=\"https:\/\/www.buzzfeednews.com\/article\/pranavdixit\/ai-generated-art-hands-fingers-messed-up\" target=\"_blank\" rel=\"noreferrer noopener\">pointed out<\/a>&nbsp;that human hands tend to be less represented in images compared to human faces, wherein the former is often unclear or shown in smaller sizes. <\/p>\n\n\n\n<p id=\"48ef\">Associate professor of AI at the University of Florida, Amelia Winger-Bearskin, also&nbsp;<a href=\"https:\/\/www.buzzfeednews.com\/article\/pranavdixit\/ai-generated-art-hands-fingers-messed-up\" target=\"_blank\" rel=\"noreferrer noopener\">says<\/a>&nbsp;that if every single image of human hands contained a full, perfect shot of hands, then the AI-reproduced versions of hands would also look perfect.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"7eb3\">Conclusion<\/h3>\n\n\n\n<p id=\"e317\">We have looked into the three reasons that contribute to the inability of AI models to emulate convincing human hands. <\/p>\n\n\n\n<p id=\"e317\">Each reason is attributed to the challenge presented by 1) the&nbsp;<em>subject<\/em>, 2) the&nbsp;<em>machine<\/em>, and 3) the&nbsp;<em>data<\/em>. There are still active research going on to address the latter two challenges.<\/p>\n\n\n\n<p id=\"f4fe\">Some may argue that because generative AIs are largely based on an algorithm that is still seemingly random to us, luck is an important factor. True enough, the currently available SOTA models can render decent-looking hands when accompanied with multiple attempts of fine-tuning the prompts.<\/p>\n\n\n\n<p id=\"f684\">However, being able to generate a typical hand would just be the beginning among many necessary milestones underway in order for a&nbsp;<em>text-to-image<\/em>&nbsp;model to live up to its name. <\/p>\n\n\n\n<p id=\"f684\">Ideally, image-generating models should be able to return results that users intended to bring \u2014 from commands like \u201cslender, delicate hands\u201d to \u201chand with six fingers including an additional thumb.\u201d This milestone presupposes a model trained to have a decent \u201cunderstanding\u201d on hands, which in turn presupposes a strong foundation backed by an aptly sized initial dataset.<\/p>\n\n\n\n<p id=\"7c03\">The generative AI in the field of images is expected to be a powerful tool as soon as these points are better addressed. <\/p>\n\n\n\n<p id=\"7c03\">As a part of this ongoing narrative, Flitto DataLab will continue to keep the conversation going.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In more ways than one, artificial intelligence (AI) image generation technology continues to amuse and terrify people in and out of the industry. The&nbsp;winning of an AI-generated art&nbsp;at a fine arts competition has brought forth fierce conversation around the genre of digital art. The artist stood by the legitimacy of his win. He&nbsp;explained&nbsp;that the quality [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":29,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[8],"tags":[9],"class_list":["post-26","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analysis","tag-artificial-intelligence"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Why do AI-generated hands look so bad?<\/title>\n<meta name=\"description\" content=\"AIs can generate eerily accurate human features, except for hands. 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