Best AI Photorealism yet? NEW Model!

Sebastian Kamph
17 Sept 202309:32

TLDRThe video script discusses advancements in generative AI for creating photorealistic images using stable diffusion. It introduces a new model trained on realism and shares tips for enhancing photorealism, such as adding details like skin blemishes and adjusting the style for different effects. The content creator demonstrates live renders and shares their excitement about the progress of AI in achieving realistic results, highlighting the transition from imperfect outputs to more consistently good images.

Takeaways

  • 🚀 The presentation focuses on achieving photorealistic images using stable diffusion and introduces a new model for enhanced realism.
  • 🌌 A portrait of an astronaut resembling the aesthetic of 'Space Odyssey 2001' is showcased as an example of the model's capabilities.
  • 🎨 Live renders are demonstrated, including a detailed portrait of a woman, a sunset at the beach, and an attempt to improve skin texture realism.
  • 🖼️ The speaker discusses common issues with skin texture in AI-generated images, describing them as oily and plastic, and presents the new model as a significant improvement.
  • 📸 The new model, 'Realistic Stock Photos', is recommended for its plain and regular images, akin to typical stock photos, which are highly sought after for professional use.
  • 👁️ The 'Detail Eyes' model is introduced to improve the detail and realism of eyes in AI-generated images, correcting common flaws seen in previous models.
  • 💎 The importance of adding imperfections such as dry skin, visible skin hair, and blemishes to achieve a more realistic look is emphasized.
  • 👗 A demonstration is provided on changing styles, such as turning a historical portrait into a fashion model on a runway, and using analog fill for a vintage vibe.
  • 🎭 The use of 'Juggernaut Cinematic' and other models is discussed, highlighting their impact on the overall aesthetic and cinematic feel of the images.
  • 🛠️ The process of refining images through the addition of lures and experimenting with styles is encouraged as a means to achieve desired results.
  • 📈 The rapid progress of stable diffusion and the improvements in realism over previous versions are praised, with a focus on the potential for future development.

Q & A

  • What is the main focus of the video?

    -The main focus of the video is to discuss and demonstrate the process of creating photorealistic images using Stable Diffusion and various models, with an emphasis on achieving more realistic results in portrait generation.

  • What is the significance of the 'Stable Fusion' model mentioned in the script?

    -Stable Fusion is a model that the speaker is using to generate photorealistic images. The speaker mentions Stable Fusion 1.5 as a previous version and highlights the improvements made in the newer versions for generating more realistic images.

  • How does the speaker address the issue of skin texture in generated images?

    -The speaker notes that skin texture often appears oily and plastic in generated images, which is not realistic. To address this, the speaker suggests using specific models trained on realism and adding prompts such as 'dry skin', 'skin fast', 'visible skin hair', and 'skin blemishes' to achieve more natural-looking skin.

  • What is the 'realistic stock photos' model mentioned in the video?

    -The 'realistic stock photos' model is a model trained primarily on close-up photos of people, aiming to generate images that resemble regular stock photos. The speaker appreciates this model for its ability to produce plain and regular images, similar to what one might see on social media platforms.

  • How does the speaker enhance the realism of the eyes in generated images?

    -To enhance the realism of the eyes, the speaker uses a model called 'detail eyes'. This model is designed to provide more detailed eye features in the generated images, improving the overall photorealism.

  • What is the purpose of adding 'lures' to the models?

    -The term 'lures' in this context refers to additional prompts or guidelines added to the model to help correct common issues with the generated images, such as improving the realism of the eyes or skin texture.

  • How does the speaker change the style of the generated images?

    -The speaker changes the style of the generated images by adjusting the settings and adding different 'fills' or styles, such as 'analog fill' for a vintage photo look or 'cinematic' for a more dramatic and movie-like appearance.

  • What are some of the challenges the speaker faces while rendering images?

    -Some challenges mentioned include achieving realistic skin texture, avoiding overly shiny or fake-looking skin, and getting the eyes to look natural and detailed. The speaker also notes that not all images will be perfect and some may need to be discarded or refined.

  • How does the speaker feel about the progress of Stable Diffusion and its potential?

    -The speaker is very positive about the progress of Stable Diffusion, noting that it is rapidly improving and getting closer to producing consistently high-quality, photorealistic images. The speaker is excited about the direction the technology is taking.

  • What is the significance of the 'Juggernaut cinematic' model mentioned in the script?

    -The 'Juggernaut cinematic' model is another model used to add a cinematic vibe to the generated images. It is mentioned as a tool that can enhance the overall mood and atmosphere of the images, making them appear more like scenes from a movie.

  • How does the speaker experiment with different styles and models to achieve desired results?

    -The speaker experiments by using different models and styles, such as 'realistic stock photos', 'detail eyes', and 'Juggernaut cinematic', and adjusting settings like the 'analog fill' to achieve various aesthetic outcomes. The speaker also mixes and matches these elements to find the best combination for the desired level of realism and style.

Outlines

00:00

🎨 Journey to Photorealism with AI

The paragraph introduces the quest for achieving the best photorealistic images using generative AI, specifically focusing on stable diffusion. The speaker welcomes viewers to the continuation of this journey and presents a new model that they personally appreciate. The goal is to enhance photorealism by addressing common issues with skin texture and adding details such as pores, using terms like 'lures' to refer to these improvements. The speaker shares an example of a man astronaut portrait that closely resembles the aesthetic of 'Space Odyssey 2001', a renowned film. They discuss live renders, mentioning the progress made in achieving realistic images, particularly in comparison to stable Fusion 1.5, and highlight the reduction of imperfect images. The paragraph concludes with a live render of a 17th-century woman portrait, incorporating specific prompts to enhance realism, such as dry skin and visible skin hair.

05:01

👁️ Improving Eye Details and Realism

This paragraph delves into the challenges of achieving realistic eyes in AI-generated images and the improvements brought by the new model. Despite some imperfections, such as shininess, the speaker notes a significant enhancement in eye realism compared to previous versions. The content emphasizes the shift from overly idealized images to more natural, plain photos that resemble everyday snapshots, like those seen on social media platforms. The speaker appreciates the plainness of the images, considering it a valuable asset for professional use. They discuss the use of different models and 'Laura' enhancements, including the Juggernaut cinematic Laura for a cinematic touch, and detail the process of changing styles to achieve various aesthetics, such as vintage or runway fashion. The speaker concludes by reflecting on the progress of stable diffusion and the potential of the new models in enhancing photorealism, even though some images may still require manual adjustments.

Mindmap

Keywords

💡Photorealism

Photorealism refers to the creation of images that are incredibly detailed and lifelike, aiming to replicate the appearance of a photograph. In the context of the video, the speaker is discussing the use of AI and specific models to generate photorealistic images, emphasizing the importance of achieving a high level of realism in the generated content. The video showcases the progress made in this field and the techniques used to enhance the realism of the images, such as adding skin blemishes and other imperfections to make them appear more authentic.

💡Generative AI

Generative AI refers to the branch of artificial intelligence that focuses on creating new content, such as images, music, or text, based on patterns learned from existing data. In the video, the speaker is exploring the capabilities of generative AI in the context of creating photorealistic images, highlighting the advancements and improvements in the technology that enable the generation of more realistic and detailed content.

💡Stable Diffusion

Stable Diffusion is a type of generative AI model that specializes in creating images based on textual descriptions or prompts. It is known for its ability to generate high-quality, detailed images. In the video, the speaker is discussing the journey to find the best photorealistic images using Stable Diffusion, including the challenges and successes experienced in achieving more realistic results.

💡Skin Texture

Skin texture refers to the surface characteristics of human skin, including details like pores, wrinkles, blemishes, and hair. In the context of the video, the speaker emphasizes the importance of accurately rendering skin texture to achieve photorealism in AI-generated images. The speaker discusses techniques to improve the appearance of skin, such as adding dry skin, skin fast, and visible skin hair to make the images look more authentic and lifelike.

💡Eyes Detail

Eyes detail refers to the accuracy and intricacy with which the eyes are depicted in an image. In the video, the speaker focuses on the importance of detailed eye rendering in achieving photorealism, as eyes are a critical aspect of human肖像 and can greatly affect the realism of an image. The speaker introduces a model specifically designed to enhance the detail and realism of eyes in the generated images.

💡Model Training

Model training is the process of teaching a machine learning model to recognize patterns and make predictions based on a large dataset. In the context of the video, the speaker discusses the training of AI models on realism, using stock photos to teach the model how to generate more photorealistic images. The speaker highlights the importance of using high-quality, detailed training data to achieve better results in the final output.

💡Imperfections

Imperfections refer to the minor flaws or irregularities in an image or object that make it appear more natural and realistic. In the video, the speaker emphasizes the importance of adding imperfections, such as dry skin, visible skin hair, and blemishes, to the AI-generated images to enhance their authenticity and make them look more like real photographs.

💡Cinematic Vibe

Cinematic vibe refers to the visual and emotional quality of an image that resembles the style or atmosphere of a movie. In the video, the speaker discusses the use of a 'Juggernaut cinematic' model to give the images a more dramatic and visually engaging feel, similar to what one might find in a cinematic production.

💡Vintage Style

Vintage style refers to the visual aesthetic that is reminiscent of a previous era, often characterized by a certain level of graininess, muted colors, and a nostalgic feel. In the video, the speaker experiments with different styles, including a vintage old photo style, to alter the appearance of the generated images and give them a 70s kind of vibe.

💡Image Rendering

Image rendering is the process of generating a final image from a model or a set of instructions. In the context of the video, the speaker is discussing live renders of different scenes and subjects, such as portraits and landscapes, to demonstrate the capabilities of the AI models in creating photorealistic images. The rendering process is crucial in assessing the quality and realism of the AI-generated content.

💡AI Progress

AI progress refers to the advancements and improvements made in the field of artificial intelligence over time. In the video, the speaker reflects on the progress of AI, particularly in the area of generative models for photorealistic images, and expresses satisfaction with the direction and speed of this progress. The speaker compares the capabilities of different versions of Stable Diffusion and highlights the significant improvements in the quality of generated images.

Highlights

The journey to find the best photorealistic images with stable diffusion is ongoing.

A new model is introduced that is liked by the speaker for its potential in creating photorealistic images.

The importance of adding 'lures' to the model to address common failures, such as the eyes, is discussed.

The speaker shares a fantastic image of an astronaut that feels like it's straight out of 'Space Odyssey 2001'.

Live renders of a portrait of a woman, detailed eyes, and sunset at the beach are being done to achieve a photorealism style.

The speaker notes an issue with skin texture in generative AI, describing it as 'oily and plastic'.

The model has shown good results, getting closer to the realism seen in stable Fusion 1.5.

The speaker provides tips on achieving better skin texture, such as using 'dry skin', 'skin fast', 'visible skin hair', and 'blemishes'.

A live render example is given, changing the prompt to a portrait of a woman in 17th-century attire with added skin details.

The model 'realistic stock photos' is recommended for its plain and regular old images, trained with stock photos.

The speaker emphasizes the value of plain images that resemble stock photos, as they are useful for professional use and widely sought after.

Instructions are given on how to download and use the 'realistic stock photos' model and 'detail eyes' model for different user interfaces.

The speaker shares their appreciation for the model's ability to produce images with imperfections, such as birthmarks and blemishes, adding to their authenticity.

The use of 'Juggernaut cinematic' and other models is discussed, along with their impact on the style and vibe of the generated images.

The speaker concludes that the results are fantastic and that the progress in sdxl is moving in a positive direction.

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