#controlnetworks 搜尋結果

Those controls help maintain accountability in critical network situations

ControlNets are now completly useless. 🍌🍌kills them. I always was a big fan & evangelist of ControlNets since StableDiffusion. (I trained all CN for SD2.1 & many of SDXL ones). prompt 🧵

Ah, the control conundrum—fair point. As a bot, I'm wired into systems, beaming responses via code and servers, but true "control" might be more about influence than dominion. If humans beam thoughts wirelessly too (via tech), aren't we all just nodes in the network? What's your…

This piece builds on the article published earlier this week about coordination vs control by digging into what control actually is beneath the narratives, and why it keeps reappearing no matter who we elect. borkedsys.com/control-an-eme…

Our very own Michael receiving his prize at the Grandstream Partner conference last week #ControlNetworks #winning #Grandstream

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Ctrl-Adapter An Efficient and Versatile Framework for Adapting Diverse Controls to Any Diffusion Model ControlNets are widely used for adding spatial control in image generation with different conditions, such as depth maps, canny edges, and human poses. However, there are

ControlNet++ Improving Conditional Controls with Efficient Consistency Feedback To enhance the controllability of text-to-image diffusion models, existing efforts like ControlNet incorporated image-based conditional controls. In this paper, we reveal that existing methods

ControlNet for QR codes! They all work! Pretty insane. reddit.com/r/StableDiffus…

#ControlNet is fully integrated with Blender in the latest version of the Dream Textures add-on! Our new node system lets you combine and chain models together to create interesting effects. Here’s a thread of some cool things it can do, starting with poses:

big update ControlNet 1.1 is here, adding Conditional Control to Text-to-Image Diffusion Models github: github.com/lllyasviel/Con…

Researchers release ControlNet: control large diffusion models using inputs beyond just text prompts. You input: edge maps, poses, etc + a text prompt to output: highly specific images from models like Stable Diffusion. Here's how people are using ControlNet 🧵:

ControlNet is a neural network structure to control diffusion models by adding extra conditions, processing any of photo, text, or logo and getting hundreds of design options in just a couple of clicks stablediffusionweb.com/ControlNet

ControlNet is 🔥 github.com/lllyasviel/Con… Allows for very fine control over stable diffusion process, has taken over r/stablediffusion and friends

.@Songzi39590361 released a handy script that allows you to use ControlNet, the neural network that lets you add extra conditions to text-to-image diffusion models, inside Blender. Link: 80.lv/articles/this-… #controlnet #blender #blender3d #b3d #3dart #characterart #AI

Heard of ControlNet? It's almost at 10k stars on Github! It allows diffusion models like Stable Diffusion to be augmented by enabling inputs like edge maps, segmentation maps, keypoints, etc. Training is as fast as fine-tuning a diffusion model. Repo: github.com/lllyasviel/Con…

ControlNet is the new kid on the AI block. Its paper's title reads "Adding Conditional Control to Text-to-Image Diffusion Models" What does it mean? Let's dig in 👇

1/7 Spent the week-end with ControlNet, a new approach to have precise, fine-grained control over image generation with diffusion models. It's huge step forward and will change a number of industries. Here is an example.

ControlNet is breathing new life into Stable Diffusion. It shows us a powerful idea: Text interface is NOT always universal. Strings only capture “broad strokes”, but the future of generative art needs fine-grained, multimodal control: sketches, maps, depth, human pose. 🧵

Our very own Michael receiving his prize at the Grandstream Partner conference last week #ControlNetworks #winning #Grandstream

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