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How to generate 3D miniature city models and animate them using Kling AI? This visual effect can be created with Kling O1, and then rotated in 3D using Image to Video. The image prompt used for generation is as follows: Present a clear, 45° top-down isometric miniature 3D cartoon...

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Kling AI

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34,303 просмотров • 8 месяцев назад •via X (Twitter)

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Have you ever imagined your city turning into a Lego world? With Kling O1, that fantasy becomes real! Tools: Kling IMAGE O1, Kling Image to Video Use this image-generation prompt: Present a clear, 45° top-down isometric miniature Lego-style 3D cartoon scene of New York built entirely from plastic bricks. Recreate the city’s most iconic landmarks and architectural elements using distinctive Lego block geometry. Use clean, glossy brick textures with subtle PBR reflections and soft, playful lighting and shadows. Keep the composition minimalistic with a soft, solid-colored background. Feeling inspired? Just change the city name and watch a whole new Lego universe come to life!
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Have you ever imagined your city turning into a Lego world? With Kling O1, that fantasy becomes real! Tools: Kling IMAGE O1, Kling Image to Video Use this image-generation prompt: Present a clear, 45° top-down isometric miniature Lego-style 3D cartoon scene of New York built entirely from plastic bricks. Recreate the city’s most iconic landmarks and architectural elements using distinctive Lego block geometry. Use clean, glossy brick textures with subtle PBR reflections and soft, playful lighting and shadows. Keep the composition minimalistic with a soft, solid-colored background. Feeling inspired? Just change the city name and watch a whole new Lego universe come to life!

Kling AI

38,391 просмотров • 8 месяцев назад

Create your city inside LovartAI ✨ Just change the names in the prompt and watch Nano Banana 2 make it real. 👀 🚨 Prompt Drop ⤵️ A street-style printed map of [ YOUR CITY ] placed on a clean light wood table, with a photorealistic miniature version of [ YOUR CITY ] emerging from it, featuring [ INSERT THE MAIN TOURIST ATTRACTIONS AND ANY CUSTOM ELEMENTS YOU WANT TO ADD ]. All elements rise organically from the map surface, forming a highly detailed 3D urban diorama. Buildings align precisely with the printed streets. Studio soft lighting, cinematic depth of field, ultra-realistic textures, clean atmosphere, premium travel photography aesthetic.
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Create your city inside LovartAI ✨ Just change the names in the prompt and watch Nano Banana 2 make it real. 👀 🚨 Prompt Drop ⤵️ A street-style printed map of [ YOUR CITY ] placed on a clean light wood table, with a photorealistic miniature version of [ YOUR CITY ] emerging from it, featuring [ INSERT THE MAIN TOURIST ATTRACTIONS AND ANY CUSTOM ELEMENTS YOU WANT TO ADD ]. All elements rise organically from the map surface, forming a highly detailed 3D urban diorama. Buildings align precisely with the printed streets. Studio soft lighting, cinematic depth of field, ultra-realistic textures, clean atmosphere, premium travel photography aesthetic.

Marcio Lima 利真 マルシオ 💎

30,701 просмотров • 5 месяцев назад

Do you want to create your cutest squeeze toy? Here is the workflow.... First create Inage with Gpt image 2 Here's the prompt modified according to your reference image and creator persona: Prompt: Ultra-realistic whimsical miniature portrait of a tiny stylized female AI creator inspired by the reference image, featuring fair glowing skin, expressive brown eyes, soft feminine facial features, dark wavy hair tied in a messy low bun with loose strands framing her face, and pearl earrings. She is standing on a polished dark wooden table with her arms at her sides, mouth wide open in a perfect "O" shape, cheeks puffed up to an exaggerated cartoon size, and eyes bulging in surprise. A giant realistic human hand enters from the right side, playfully poking her exposed belly, causing a funny squishy reaction. She wears an oversized black Future Vibes AI hoodie, relaxed beige trousers, and white sneakers. The character has adorable bobblehead proportions with a disproportionately large head and tiny body, soft rubbery Pixar-style physics, photorealistic skin textures, expressive facial animation, and cute miniature details. Background is a clean light grey/off-white horizontal panel wall with soft diffused indoor lighting and subtle shadows beneath the figure. Vertical composition, medium close-up shot, centered framing, whimsical cinematic atmosphere, ultra-detailed 3D render, Pixar meets realism, shallow depth of field, 8K masterpiece. Image Created In Vidu AI For Video Prompt Check Below
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Do you want to create your cutest squeeze toy? Here is the workflow.... First create Inage with Gpt image 2 Here's the prompt modified according to your reference image and creator persona: Prompt: Ultra-realistic whimsical miniature portrait of a tiny stylized female AI creator inspired by the reference image, featuring fair glowing skin, expressive brown eyes, soft feminine facial features, dark wavy hair tied in a messy low bun with loose strands framing her face, and pearl earrings. She is standing on a polished dark wooden table with her arms at her sides, mouth wide open in a perfect "O" shape, cheeks puffed up to an exaggerated cartoon size, and eyes bulging in surprise. A giant realistic human hand enters from the right side, playfully poking her exposed belly, causing a funny squishy reaction. She wears an oversized black Future Vibes AI hoodie, relaxed beige trousers, and white sneakers. The character has adorable bobblehead proportions with a disproportionately large head and tiny body, soft rubbery Pixar-style physics, photorealistic skin textures, expressive facial animation, and cute miniature details. Background is a clean light grey/off-white horizontal panel wall with soft diffused indoor lighting and subtle shadows beneath the figure. Vertical composition, medium close-up shot, centered framing, whimsical cinematic atmosphere, ultra-detailed 3D render, Pixar meets realism, shallow depth of field, 8K masterpiece. Image Created In Vidu AI For Video Prompt Check Below

Future Vibes AI - Educator

21,345 просмотров • 1 месяц назад

Here's exactly how to create these 3D Animations in under 5 minutes: 1. Generate character with GPT using this prompt: 9X16 image of a 3D hyper-realistic character of (DESIRED CHARACTER), anthropomorphic with a friendly face and large expressive eyes. Unreal Engine 5 render style. Background is a (DESIRED BACKGROUND) 2. Animate the video with VEO 3 3. Clone the entire entire video's voice with elevenlabs and rewrite the entire audio clip and paste it back in with capcut. Thats it, stop wasting money on 3D artists.
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Here's exactly how to create these 3D Animations in under 5 minutes: 1. Generate character with GPT using this prompt: 9X16 image of a 3D hyper-realistic character of (DESIRED CHARACTER), anthropomorphic with a friendly face and large expressive eyes. Unreal Engine 5 render style. Background is a (DESIRED BACKGROUND) 2. Animate the video with VEO 3 3. Clone the entire entire video's voice with elevenlabs and rewrite the entire audio clip and paste it back in with capcut. Thats it, stop wasting money on 3D artists.

mtvmald

66,085 просмотров • 5 месяцев назад

Google Earth now lets you create AI images using real-world locations. With the new Nano Banana AI feature, you can pick any place in Google Earth, click “Create Image,” and describe what you want to see. The AI can turn that location into a historical scene, a futuristic city or a fantasy world The feature uses Google Earth’s satellite and 3D map data as the base, so the AI-generated images are built from real locations.
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Google Earth now lets you create AI images using real-world locations. With the new Nano Banana AI feature, you can pick any place in Google Earth, click “Create Image,” and describe what you want to see. The AI can turn that location into a historical scene, a futuristic city or a fantasy world The feature uses Google Earth’s satellite and 3D map data as the base, so the AI-generated images are built from real locations.

Pirat_Nation 🔴

24,731 просмотров • 8 дней назад

kling 2.6 motion control is actually insane for AI ads you can swap any person in a video with a different person and it looks completely realistic, and its way better than wan 2.2 this unlocks massive testing potential for ads you can test the same ad concept across multiple different ICPs instantly here's the workflow: >generate your new character with nano banana pro >use kling 2.6 motion control to replace the person in your existing video generate a new voice with >elevenlabs to match the character you can take one winning ad and instantly create 10 variations targeting: -different age groups -different genders -different ethnicities -different aesthetics this is the future of ad testing at scale
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kling 2.6 motion control is actually insane for AI ads you can swap any person in a video with a different person and it looks completely realistic, and its way better than wan 2.2 this unlocks massive testing potential for ads you can test the same ad concept across multiple different ICPs instantly here's the workflow: >generate your new character with nano banana pro >use kling 2.6 motion control to replace the person in your existing video generate a new voice with >elevenlabs to match the character you can take one winning ad and instantly create 10 variations targeting: -different age groups -different genders -different ethnicities -different aesthetics this is the future of ad testing at scale

Miko

29,396 просмотров • 7 месяцев назад

DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion TL;DR: Create 3/4DGS from Video Diffusion Note: Some first inference code released (not all yet). Contributions (cited): • We present DimensionX, a novel framework for generating photorealistic 3D and 4D scenes from only a single image using controllable video diffusion. • We propose ST-Director, which decouples the spatial and temporal priors in video diffusion models by learning (spatial and temporal) dimension-aware modules with our curated datasets. We further enhance the hybriddimension control with a training-free composition approach according to the essence of video diffusion denoising process. • To bridge the gap between video diffusion and real-world scenes, we design a trajectory-aware mechanism for 3D generation and an identity-preserving denoising approach for 4D generation, enabling more realistic and controllable scene synthesis. • Extensive experiments manifest that our DimensionX delivers superior performance in video, 3D, and 4D generation compared with baseline methods.
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DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion TL;DR: Create 3/4DGS from Video Diffusion Note: Some first inference code released (not all yet). Contributions (cited): • We present DimensionX, a novel framework for generating photorealistic 3D and 4D scenes from only a single image using controllable video diffusion. • We propose ST-Director, which decouples the spatial and temporal priors in video diffusion models by learning (spatial and temporal) dimension-aware modules with our curated datasets. We further enhance the hybriddimension control with a training-free composition approach according to the essence of video diffusion denoising process. • To bridge the gap between video diffusion and real-world scenes, we design a trajectory-aware mechanism for 3D generation and an identity-preserving denoising approach for 4D generation, enabling more realistic and controllable scene synthesis. • Extensive experiments manifest that our DimensionX delivers superior performance in video, 3D, and 4D generation compared with baseline methods.

MrNeRF

17,052 просмотров • 1 год назад

Create a 3D model from a single image, set of images or a text prompt in < 1 minute 😮‍💨 This new AI paper called CAT3D shows us that it’ll keep getting easier to produce 3D models from 2D images — whether it’s a sparser real world 3D scan (a few photos instead of hundreds) or your favorite 2D image generator like Midjourney (just an image). How does this magic work? “This architecture is similar to video diffusion models, but with camera pose embeddings for each image instead of time embeddings. The generated views are passed into a robust 3D reconstruction pipeline to create the 3D representation (Zip-NeRF or 3DGS)”
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Create a 3D model from a single image, set of images or a text prompt in < 1 minute 😮‍💨 This new AI paper called CAT3D shows us that it’ll keep getting easier to produce 3D models from 2D images — whether it’s a sparser real world 3D scan (a few photos instead of hundreds) or your favorite 2D image generator like Midjourney (just an image). How does this magic work? “This architecture is similar to video diffusion models, but with camera pose embeddings for each image instead of time embeddings. The generated views are passed into a robust 3D reconstruction pipeline to create the 3D representation (Zip-NeRF or 3DGS)”

Bilawal Sidhu

92,792 просмотров • 2 лет назад

A quick test of using 3d drawing with 6DOF controllers as an "instructor" for a generative AI process. There's so many powerful and fun new ways to create just around the corner.. Here I'm using Dreams, Krea and 3daistudio. The 3d model at the end of the video was generated from the Dreams+Krea output in just around 15 seconds. Only the model on the left is a "true" 3d model. #ai #madeindreams
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A quick test of using 3d drawing with 6DOF controllers as an "instructor" for a generative AI process. There's so many powerful and fun new ways to create just around the corner.. Here I'm using Dreams, Krea and 3daistudio. The 3d model at the end of the video was generated from the Dreams+Krea output in just around 15 seconds. Only the model on the left is a "true" 3d model. #ai #madeindreams

Martin Nebelong

132,864 просмотров • 2 лет назад

ChatGPT-Image-2.0 × HappyHorse 1.0 作り方： Step 1：ChatGPT-Image-2.0で画面を生成 Prompt Step-by-step shampoo routine: first create enough foam in your hands; do not apply shampoo directly to the scalp; apply the foam to the scalp and gently cleanse. Rinse thoroughly with water, then dry at the end. Clean bathroom background, soft lighting, instructional style, photorealistic, high detail Step 2：HappyHorse 1.0で動画化 Prompt Share 124 Following steps in the reference image, a step-by-step shampoo routine: first create enough foam in your hands; do not apply shampoo directly to the scalp; apply the foam to the scalp and gently cleanse. Rinse thoroughly with water, then dry at the end. Clean bathroom background, soft lighting, instructional style, photorealistic, high detail
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ChatGPT-Image-2.0 × HappyHorse 1.0 作り方： Step 1：ChatGPT-Image-2.0で画面を生成 Prompt Step-by-step shampoo routine: first create enough foam in your hands; do not apply shampoo directly to the scalp; apply the foam to the scalp and gently cleanse. Rinse thoroughly with water, then dry at the end. Clean bathroom background, soft lighting, instructional style, photorealistic, high detail Step 2：HappyHorse 1.0で動画化 Prompt Share 124 Following steps in the reference image, a step-by-step shampoo routine: first create enough foam in your hands; do not apply shampoo directly to the scalp; apply the foam to the scalp and gently cleanse. Rinse thoroughly with water, then dry at the end. Clean bathroom background, soft lighting, instructional style, photorealistic, high detail

KANA｜東京AI映像

22,601 просмотров • 3 месяцев назад

Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.
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Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.

MrNeRF

52,849 просмотров • 1 год назад

What used to take lights, props, and a full set can now be done inside an agent. This was created using a Glif agent with Kling 2.6 Motion Control and a Nano Banana reference image to lock the look. No physical setup needed. Glif has agents for different creative use cases, so you can pick what fits your workflow and move fast. Check the agents used for this below 👇
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What used to take lights, props, and a full set can now be done inside an agent. This was created using a Glif agent with Kling 2.6 Motion Control and a Nano Banana reference image to lock the look. No physical setup needed. Glif has agents for different creative use cases, so you can pick what fits your workflow and move fast. Check the agents used for this below 👇

GLIF

12,858 просмотров • 7 месяцев назад

Created this by using a movement sheet as a reference image to animate the dance using Seedance 2.0 + ChatGPT image 2.0 on Yapper GPT Image 2.0 Prompt: Dance Sequence Instruction Sheet [VISUAL STYLE] A composition featuring a highly detailed 3D-rendered female dancer. Designed like a professional choreography guide with a technical, diagram-inspired layout. Clean white background, soft studio lighting, and strong contrast to highlight body movement and posture. [GRID LAYOUT] Structured 4×4 panel grid (16 frames total), evenly spaced with thin black divider lines. Each panel is identical in size and clearly numbered from 1 to 16 to show a continuous dance progression. [CHARACTER] Use image1 as the base character. The same female dancer appears consistently across all panels with accurate likeness and proportions. [WARDROBE] The dancer wears a stylish, performance-ready outfit: a well-fitted top paired with a short, flowy skirt. The look should feel modern and visually appealing while still practical for dance movement. Fabric should subtly respond to motion (slight flow and folds), even in grayscale. [PANEL STRUCTURE – EACH FRAME] Top-left: Step number + short dance move title (e.g., “Step 5 – Spin Transition”) Center: Full-body pose capturing a precise moment in the choreography Bottom-left: 3–4 lines of concise instruction describing the move Overlay: Motion arrows and directional guides illustrating how the dancer transitions [MOTION INDICATORS] Incorporate curved arrows for fluid motion, straight arrows for directional steps, and circular indicators for spins or turns. Emphasize rhythm, weight shifts, and body isolation. [RENDER QUALITY] High-detail sculpted 3D style with smooth grayscale shading, subtle shadows, and clean linework. Maintain a polished, concept-art level finish with clarity in every pose. [RESTRICTIONS] No color, no background scenery, no extra characters, no visual clutter, only the dancer and instructional elements.
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Created this by using a movement sheet as a reference image to animate the dance using Seedance 2.0 + ChatGPT image 2.0 on Yapper GPT Image 2.0 Prompt: Dance Sequence Instruction Sheet [VISUAL STYLE] A composition featuring a highly detailed 3D-rendered female dancer. Designed like a professional choreography guide with a technical, diagram-inspired layout. Clean white background, soft studio lighting, and strong contrast to highlight body movement and posture. [GRID LAYOUT] Structured 4×4 panel grid (16 frames total), evenly spaced with thin black divider lines. Each panel is identical in size and clearly numbered from 1 to 16 to show a continuous dance progression. [CHARACTER] Use image1 as the base character. The same female dancer appears consistently across all panels with accurate likeness and proportions. [WARDROBE] The dancer wears a stylish, performance-ready outfit: a well-fitted top paired with a short, flowy skirt. The look should feel modern and visually appealing while still practical for dance movement. Fabric should subtly respond to motion (slight flow and folds), even in grayscale. [PANEL STRUCTURE – EACH FRAME] Top-left: Step number + short dance move title (e.g., “Step 5 – Spin Transition”) Center: Full-body pose capturing a precise moment in the choreography Bottom-left: 3–4 lines of concise instruction describing the move Overlay: Motion arrows and directional guides illustrating how the dancer transitions [MOTION INDICATORS] Incorporate curved arrows for fluid motion, straight arrows for directional steps, and circular indicators for spins or turns. Emphasize rhythm, weight shifts, and body isolation. [RENDER QUALITY] High-detail sculpted 3D style with smooth grayscale shading, subtle shadows, and clean linework. Maintain a polished, concept-art level finish with clarity in every pose. [RESTRICTIONS] No color, no background scenery, no extra characters, no visual clutter, only the dancer and instructional elements.

Johnn

54,611 просмотров • 3 месяцев назад

We are getting absurdly close to the point where “learning Blender” means learning how to direct an AI. A shot like this looks soft and playful on the surface, but under it is the usual 3D pain: modeling, layout, materials, lighting, atmosphere, animation, and endless tiny fixes until the frame stops looking dead. That is why Kimi K3 matters. With Blender MCP, you can describe a scene like a robotic goat walking through a dreamy field and let the model help build the environment, place the camera, shape the materials, script the motion, and iterate inside the real Blender project. The real shift is not text-to-image. It is text-to-workflow. Kimi K3 does not just give you a pretty output and disappear. It can help move the actual scene from rough setup to something that looks art-directed. Soon the hardest part of 3D will not be the software. It will be whether your imagination is good enough to deserve tools like this.
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We are getting absurdly close to the point where “learning Blender” means learning how to direct an AI. A shot like this looks soft and playful on the surface, but under it is the usual 3D pain: modeling, layout, materials, lighting, atmosphere, animation, and endless tiny fixes until the frame stops looking dead. That is why Kimi K3 matters. With Blender MCP, you can describe a scene like a robotic goat walking through a dreamy field and let the model help build the environment, place the camera, shape the materials, script the motion, and iterate inside the real Blender project. The real shift is not text-to-image. It is text-to-workflow. Kimi K3 does not just give you a pretty output and disappear. It can help move the actual scene from rough setup to something that looks art-directed. Soon the hardest part of 3D will not be the software. It will be whether your imagination is good enough to deserve tools like this.

Rina

45,651 просмотров • 12 дней назад

next, here is how to animate the video once you generated the base image of your ai model, attach the image of your model and the product image in your ai tool and prompt, "she is holding this product" now to animate this scene, use such a simple prompt; "the girl is speaking in her beautiful voice; "this is the most powerful drink in the world... drink it once, and your whole hair is gone" no background music, no sound effects." adding "no background music" is necessory part when you're prompting to VEO 3 or Kling 2.6 and for the drinking scene, i also gave it a very simple prompt; "the girl is drinking, handheld camera shaking. No background music," then i asked nb pro to remove her hair, and then turn it into the using that simple prompt method. note; simple prompts works better than complicated one when it comes to animating your video that's it, if you need any help setting up your ai influencer to promote your product/app or service just DM me here on 𝕏 or comment "want" i'll dm you myself if you know how to make viral content + setup such a beautiful ai model 2026 will be yours, cheers
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next, here is how to animate the video once you generated the base image of your ai model, attach the image of your model and the product image in your ai tool and prompt, "she is holding this product" now to animate this scene, use such a simple prompt; "the girl is speaking in her beautiful voice; "this is the most powerful drink in the world... drink it once, and your whole hair is gone" no background music, no sound effects." adding "no background music" is necessory part when you're prompting to VEO 3 or Kling 2.6 and for the drinking scene, i also gave it a very simple prompt; "the girl is drinking, handheld camera shaking. No background music," then i asked nb pro to remove her hair, and then turn it into the using that simple prompt method. note; simple prompts works better than complicated one when it comes to animating your video that's it, if you need any help setting up your ai influencer to promote your product/app or service just DM me here on 𝕏 or comment "want" i'll dm you myself if you know how to make viral content + setup such a beautiful ai model 2026 will be yours, cheers

ViralOps

21,545 просмотров • 8 месяцев назад

Smartest AI update for Chrome You can now use Gemini from anywhere: - Type "@" in the top bar - Select "Chat with Gemini" - Write your prompt next Press Enter and Chrome will answer you directly using Gemini! No longer need to open a new tab, access Gemini and then finally type your prompt. Everything is done directly from the top bar in one go: a huge productivity boost!
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Smartest AI update for Chrome You can now use Gemini from anywhere: - Type "@" in the top bar - Select "Chat with Gemini" - Write your prompt next Press Enter and Chrome will answer you directly using Gemini! No longer need to open a new tab, access Gemini and then finally type your prompt. Everything is done directly from the top bar in one go: a huge productivity boost!

Paul Couvert

62,465 просмотров • 2 лет назад

As announced in partnership with NVIDIA at CES, we’re excited to introduce Stable Point Aware 3D (SPAR3D), setting a new standard in 3D generation. Ideal for running on NVIDIA RTX AI PCs, SPAR3D enables real-time editing and complete structure generation of 3D objects from a single image in under a second. You can download the weights on Hugging Face and code on GitHub, or access the model through the Stability AI API. Learn more here: (1/3)
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As announced in partnership with NVIDIA at CES, we’re excited to introduce Stable Point Aware 3D (SPAR3D), setting a new standard in 3D generation. Ideal for running on NVIDIA RTX AI PCs, SPAR3D enables real-time editing and complete structure generation of 3D objects from a single image in under a second. You can download the weights on Hugging Face and code on GitHub, or access the model through the Stability AI API. Learn more here: (1/3)

Stability AI

181,479 просмотров • 1 год назад

Just testing Nano Banana for fashion try on + changing facial expressions and poses and then Kling AI 2.1 start and end frame to create outfit changes. It could be an interesting way to showcase fashion items on a website. Maybe a new range of clothing got released and you can create transitions that showcase every new item OR if you've done real photography with real models wearing real items of clothing, you can just create transitions between the outfits to showcase them. The main way I'm prompting on Kling using start and end frame to get these effects is to say something like "A womans outfit rapidly changes" or "A womans outfit rapidly changes from a burst of fire, sparks and smoke".
0:14

Just testing Nano Banana for fashion try on + changing facial expressions and poses and then Kling AI 2.1 start and end frame to create outfit changes. It could be an interesting way to showcase fashion items on a website. Maybe a new range of clothing got released and you can create transitions that showcase every new item OR if you've done real photography with real models wearing real items of clothing, you can just create transitions between the outfits to showcase them. The main way I'm prompting on Kling using start and end frame to get these effects is to say something like "A womans outfit rapidly changes" or "A womans outfit rapidly changes from a burst of fire, sparks and smoke".

Travis Davids

11,686 просмотров • 11 месяцев назад

✨ I can now generate 3d assets for my drone sim at directly from Cursor (sponsor of #vibejam) I need buildings that you'd see in a war torn city, like warehouses in ruins, broken down abandoned houses, bombed out bridges etc. Nano Banana Pro or 2 can generate them really well and then you can put them in an image-to-3d model and you get a GLB or FBX That one you can then import into your Three.js game, the models might be big though, in my case like 16MB, so I ask it to compress it and make it more low poly so it loads fast ThreeJS then loads the individual GLBs on page load and puts them in my drone sim somewhere randomly, I think I should remove some of the grass and match the sandy color of the ruins though to make it fit in more
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✨ I can now generate 3d assets for my drone sim at directly from Cursor (sponsor of #vibejam) I need buildings that you'd see in a war torn city, like warehouses in ruins, broken down abandoned houses, bombed out bridges etc. Nano Banana Pro or 2 can generate them really well and then you can put them in an image-to-3d model and you get a GLB or FBX That one you can then import into your Three.js game, the models might be big though, in my case like 16MB, so I ask it to compress it and make it more low poly so it loads fast ThreeJS then loads the individual GLBs on page load and puts them in my drone sim somewhere randomly, I think I should remove some of the grass and match the sandy color of the ruins though to make it fit in more

@levelsio

134,777 просмотров • 3 месяцев назад

MiniMax H3 is incredible at text rendering! This is a text to video prompt! Prompt : Create a 15-second cinematic text-animation video built around the quote: “Every great change begins quietly, grows through courage, and becomes impossible to ignore.” The quote should appear gradually as a visual story. Each new phrase must transform the design, atmosphere, movement, and emotional intensity of the scene. Use elegant typography, accurate spelling, cinematic lighting, smooth transitions, and perfectly readable text. 0:00–0:03 | “Every great change” Begin with a completely black screen. A tiny point of warm light slowly appears in the center, like the first spark of an idea. The words “Every great change” emerge softly from the darkness, one word at a time. Use thin, elegant serif typography with wide letter spacing. “Every” fades in gently. “Great” grows slightly larger. “Change” forms from small drifting particles that gather into solid letters. Keep the scene quiet, minimal, and mysterious. 0:03–0:06 | “begins quietly,” The camera slowly moves closer to the text. The previous words shrink and reposition toward the upper-left corner as the phrase “begins quietly,” appears in delicate lowercase letters. Animate the phrase as though it is being written by an invisible hand. Each letter should create a subtle ripple in the darkness. Introduce faint textures, soft shadows, floating dust, and gentle light rays. The comma should appear last and create a small circular pulse. 0:06–0:09 | “grows through courage,” The pulse expands and transforms the scene from darkness into a rich sunrise gradient with deep orange, red, and golden tones. The words “grows through courage” rise upward from the bottom of the frame. Animate “grows” by gradually increasing its size and weight. Animate “through” along a curved path. Animate “courage” in bold uppercase letters that push through a translucent barrier, causing it to crack into geometric fragments. The movement should feel powerful but controlled. 0:09–0:12 | “and becomes” The fragments rotate in slow motion and reorganize into a clean editorial grid. The phrase “AND BECOMES” appears across the frame in condensed sans-serif typography. Animate the letters with fast tracking changes, vertical stretching, masking, and perspective movement. The camera accelerates forward through the center of the word “BECOMES.” The sound and visual energy should steadily build. 0:12–0:14 | “impossible to ignore.” Reveal a vast bright space filled with light, moving shapes, and large-scale typography. The words “IMPOSSIBLE TO IGNORE” appear one after another. “IMPOSSIBLE” expands beyond the edges of the screen. “TO” remains small and perfectly centered. “IGNORE” slams into place with strong visual impact, briefly shaking the surrounding grid and shapes. Use bold contrast, dramatic scale, sharp shadows, and synchronized motion. 0:14–0:15 | Final quote All movement stops instantly. The complete quote appears centered on a clean off-white background: “Every great change begins quietly, grows through courage, and becomes impossible to ignore.” Use refined black typography with “change,” “courage,” and “impossible” highlighted in deep red. Hold the final composition clearly for the last second. Maintain one continuous visual journey from darkness to light, silence to impact, and simplicity to complexity. Keep every phrase connected through visual transformations rather than hard cuts. Use realistic motion blur, precise kerning, clean masks, stable letterforms, smooth camera movement, subtle film grain, cinematic sound design, rising ambient music, soft particles, controlled color transitions, and a final deep impact sound. Avoid misspelled words, warped letters, duplicated characters, unreadable text, random symbols, excessive flickering, chaotic layouts, inconsistent fonts.
0:15

MiniMax H3 is incredible at text rendering! This is a text to video prompt! Prompt : Create a 15-second cinematic text-animation video built around the quote: “Every great change begins quietly, grows through courage, and becomes impossible to ignore.” The quote should appear gradually as a visual story. Each new phrase must transform the design, atmosphere, movement, and emotional intensity of the scene. Use elegant typography, accurate spelling, cinematic lighting, smooth transitions, and perfectly readable text. 0:00–0:03 | “Every great change” Begin with a completely black screen. A tiny point of warm light slowly appears in the center, like the first spark of an idea. The words “Every great change” emerge softly from the darkness, one word at a time. Use thin, elegant serif typography with wide letter spacing. “Every” fades in gently. “Great” grows slightly larger. “Change” forms from small drifting particles that gather into solid letters. Keep the scene quiet, minimal, and mysterious. 0:03–0:06 | “begins quietly,” The camera slowly moves closer to the text. The previous words shrink and reposition toward the upper-left corner as the phrase “begins quietly,” appears in delicate lowercase letters. Animate the phrase as though it is being written by an invisible hand. Each letter should create a subtle ripple in the darkness. Introduce faint textures, soft shadows, floating dust, and gentle light rays. The comma should appear last and create a small circular pulse. 0:06–0:09 | “grows through courage,” The pulse expands and transforms the scene from darkness into a rich sunrise gradient with deep orange, red, and golden tones. The words “grows through courage” rise upward from the bottom of the frame. Animate “grows” by gradually increasing its size and weight. Animate “through” along a curved path. Animate “courage” in bold uppercase letters that push through a translucent barrier, causing it to crack into geometric fragments. The movement should feel powerful but controlled. 0:09–0:12 | “and becomes” The fragments rotate in slow motion and reorganize into a clean editorial grid. The phrase “AND BECOMES” appears across the frame in condensed sans-serif typography. Animate the letters with fast tracking changes, vertical stretching, masking, and perspective movement. The camera accelerates forward through the center of the word “BECOMES.” The sound and visual energy should steadily build. 0:12–0:14 | “impossible to ignore.” Reveal a vast bright space filled with light, moving shapes, and large-scale typography. The words “IMPOSSIBLE TO IGNORE” appear one after another. “IMPOSSIBLE” expands beyond the edges of the screen. “TO” remains small and perfectly centered. “IGNORE” slams into place with strong visual impact, briefly shaking the surrounding grid and shapes. Use bold contrast, dramatic scale, sharp shadows, and synchronized motion. 0:14–0:15 | Final quote All movement stops instantly. The complete quote appears centered on a clean off-white background: “Every great change begins quietly, grows through courage, and becomes impossible to ignore.” Use refined black typography with “change,” “courage,” and “impossible” highlighted in deep red. Hold the final composition clearly for the last second. Maintain one continuous visual journey from darkness to light, silence to impact, and simplicity to complexity. Keep every phrase connected through visual transformations rather than hard cuts. Use realistic motion blur, precise kerning, clean masks, stable letterforms, smooth camera movement, subtle film grain, cinematic sound design, rising ambient music, soft particles, controlled color transitions, and a final deep impact sound. Avoid misspelled words, warped letters, duplicated characters, unreadable text, random symbols, excessive flickering, chaotic layouts, inconsistent fonts.

Umesh

20,586 просмотров • 6 дней назад