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An image + a detailed normal map generated by GeoWizard --> a relightable image. Geowizard is a generative geometry estimation model that could jointly produce high-quality depth and normal with intricate details. Try our huggingface demo here: #huggingface #gradio #geowizard

Xiao-Xiao Long

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30,338 次观看 • 2 年前 •via X (Twitter)

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Hi3DGen 🔥 High-fidelity 3D geometry generation from a single image by leveraging normal maps as an intermediate representation

Hi3DGen 🔥 High-fidelity 3D geometry generation from a single image by leveraging normal maps as an intermediate representation

Gradio

50,996 次观看 • 1 年前

I added a node to my custom node that converts the depth image to a normal map! This is useful for 2D-style images where Normals Estimation doesn't work well.

I added a node to my custom node that converts the depth image to a normal map! This is useful for 2D-style images where Normals Estimation doesn't work well.

toyxyz

117,354 次观看 • 1 年前

I created a simple GUI to use Depth to Normal without ComfyUI! Once you input an image, it will be exported as a .glTF with a normal map. Import it directly into your favorite tool like Blender or CSP. #AI :

I created a simple GUI to use Depth to Normal without ComfyUI! Once you input an image, it will be exported as a .glTF with a normal map. Import it directly into your favorite tool like Blender or CSP. #AI :

toyxyz

29,371 次观看 • 1 年前

Fun & likely unintended use case for #NanoBananaPro: image→3D point cloud Prompt: This is a rendering of a 3D model of a person. Make an accurate image of the corresponding normal map. Then I run Poisson-based normals→3D Pretty amazing for a general-purpose 2D image model 🤩

Fun & likely unintended use case for #NanoBananaPro: image→3D point cloud Prompt: This is a rendering of a 3D model of a person. Make an accurate image of the corresponding normal map. Then I run Poisson-based normals→3D Pretty amazing for a general-purpose 2D image model 🤩

Keenan Crane

71,561 次观看 • 7 个月前

名画を立体的に鑑賞する方法 Nano Banana Pro (深度/法線マップ生成)→ WebGL(Three.js) スマホでも体験できます👉 【プロンプト】（法線マップ用） Generate a surface normal map from the input artwork image. Output one RGB image where each pixel encodes the surface normal direction in standard tangent-space format: •R = X direction •G = Y direction •B = Z direction Requirements: •Maintain the same resolution and aspect ratio as the input image. •Normal directions must follow the local geometry implied by brush strokes, shading, and contours. •Do NOT add new artistic elements or repaint the scene. •Only infer plausible micro-geometry and surface orientation. •Ensure smooth, consistent normal transitions without noise. （深度マップ用） Generate a depth map from the input artwork image. Output a single grayscale depth map where: •White = near to the viewer •Black = far from the viewer Requirements: •Maintain the same resolution and aspect ratio as the input image. •Depth must be smooth, continuous, and physically plausible. •Infer only geometric depth that could reasonably exist in the original artwork. •Do NOT add new objects or details. •Do NOT stylize, repaint, or reinterpret the scene. •Avoid texture noise; focus solely on depth structure.

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ハシモトタクマ / FunTech

27,192 次观看 • 7 个月前

Google just revealed an ABSOLUTE depth estimation model 🤯 As opposed to recent depth models (Marigold, PatchFusion) which aim for maximum details, DMD aims to estimate the ABSOLUTE depth (in meters) within the image More details below ⬇️⬇️

Google just revealed an ABSOLUTE depth estimation model 🤯 As opposed to recent depth models (Marigold, PatchFusion) which aim for maximum details, DMD aims to estimate the ABSOLUTE depth (in meters) within the image More details below ⬇️⬇️

Alex Carlier

199,524 次观看 • 2 年前

Leffa from Meta is a 🆕 unified framework for controllable person image generation that enables precise manipulation of both appearance (i.e., Virtual try-on) and pose (i.e., Pose transfer). Learn more about 📚 Code,🔥 Demo, and 🤗 Model ⬇️

Leffa from Meta is a 🆕 unified framework for controllable person image generation that enables precise manipulation of both appearance (i.e., Virtual try-on) and pose (i.e., Pose transfer). Learn more about 📚 Code,🔥 Demo, and 🤗 Model ⬇️

Gradio

52,913 次观看 • 1 年前

NVidia just released PiD: super resolution in pixel space directly from model latents 🔎 4X resolution for any generated image, FAST! 🏎️💨 FLUX.1, 2 and Z-Image (Qwen Image coming) of course, i built a demo: generate 4K images with Z-Image

NVidia just released PiD: super resolution in pixel space directly from model latents 🔎 4X resolution for any generated image, FAST! 🏎️💨 FLUX.1, 2 and Z-Image (Qwen Image coming) of course, i built a demo: generate 4K images with Z-Image

apolinario (poli)

29,948 次观看 • 1 个月前

🆕 Image super-resolution model just dropped! Superior results even with a single sampling step. 🔥InvSR: Arbitrary-steps Image Super-resolution via Diffusion Inversion.

🆕 Image super-resolution model just dropped! Superior results even with a single sampling step. 🔥InvSR: Arbitrary-steps Image Super-resolution via Diffusion Inversion.

Gradio

53,331 次观看 • 1 年前

😀 ToonCrafter: Generative Cartoon Interpolation 🔆 Can interpolate two cartoon images by leveraging the pre-trained image-to-video diffusion priors. Model on 🤗👇

😀 ToonCrafter: Generative Cartoon Interpolation 🔆 Can interpolate two cartoon images by leveraging the pre-trained image-to-video diffusion priors. Model on 🤗👇

Gradio

93,074 次观看 • 2 年前

Huggingface has entered their node editor era with Daggr (DAG-based Gradio workflows). Really really cool and well done

Huggingface has entered their node editor era with Daggr (DAG-based Gradio workflows). Really really cool and well done

Andrew Carr 🤸

29,325 次观看 • 5 个月前

A single image generated by GPT Image 2, combined with Seedance 2.0, can already achieve this kind of effect Below is the Image 2 prompt👇

A single image generated by GPT Image 2, combined with Seedance 2.0, can already achieve this kind of effect Below is the Image 2 prompt👇

Ai Arainz

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Yesss Jasper introduces LBM: Latent Bridge Matching for Fast Image-to-Image Translation💡 and drops an amazing ✨image relighting✨ demo that runs with a single(!) inference step 🔥

Yesss Jasper introduces LBM: Latent Bridge Matching for Fast Image-to-Image Translation💡 and drops an amazing ✨image relighting✨ demo that runs with a single(!) inference step 🔥

Linoy Tsaban

14,426 次观看 • 1 年前

You can now Remix your images 🎨 Click the Remix icon below your generated image and Venice will generate a similar image with some details and characteristics "remixed"

You can now Remix your images 🎨 Click the Remix icon below your generated image and Venice will generate a similar image with some details and characteristics "remixed"

Venice

14,923 次观看 • 9 个月前

World Models are heating up as Prof. Fei-fei Li Fei-Fei Li's World Labs World Labs ignites the space with their first product Marble 🔥🌍 Riding that momentum, we’re launching a World Model demo on Theta Network EdgeCloud, powered by Tencent Tencent 腾讯's open-source Hunyuan 3D World Model, and packaged as a standard model template for creators, devs, and AI worldbuilders. Text/Image → explorable 3D worlds. Single image → full geometry. Exportable, editable, fast! Try it now:

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Runware

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Industrial CT scans capture both geometry and relative density. We start by taking hundreds of X-ray images from different angles, then reconstruct them into a 3D model that can be sectioned and analyzed. A dark area in a 2D X-ray image could be either thicker material or denser material; by rotating the object we’re scanning, we can separate geometry from density. In this Lumafield CT scan, density is visualized as a blue-red color map.

Industrial CT scans capture both geometry and relative density. We start by taking hundreds of X-ray images from different angles, then reconstruct them into a 3D model that can be sectioned and analyzed. A dark area in a 2D X-ray image could be either thicker material or denser material; by rotating the object we’re scanning, we can separate geometry from density. In this Lumafield CT scan, density is visualized as a blue-red color map.

Jon Bruner

79,466 次观看 • 1 年前

from a single image, an entire video—preserving face (finally!), style, and mood. all generated on freepik. new flux model rocks.

from a single image, an entire video—preserving face (finally!), style, and mood. all generated on freepik. new flux model rocks.

Omar Pera

12,326 次观看 • 1 年前