Today, we’re introducing Meta’s latest 3D foundation model, AssetGen... 2.0, which was designed to create high-quality 3D assets from text and image prompts. AssetGen 2.0 consists of two models developed within Meta: one to generate 3D meshes and another to generate textures. Read More:show more

This is RICULOUSLY good, TRELLIS 3D Generation model by... Microsoft! 🔥 Generate high-quality 3D assets from text or image prompts. Supports various formats like Radiance Fields, 3D Gaussians, and meshes Available for FREE on Hugging Face!show more

2025 is year of 3D AI Rodin AI 1.5... now can not only generate 3D model with clean meshes but also create high quality textures You can export all the models to 3D software to create a new worldshow more

NVIDIA introduces Edify 3D AI model You can generate... high quality 3D assets from text or image input under 2 minutes! With PBR materials, quad-mesh topologies, and 4k textures. 6 wild examples:show more

🚀Rodin Gen-1 is the largest 3D-native #GenerativeAI, which is... same as #SD. Besides its ability to generate #3D model and #PBR material, it can also creates objects from simple shapes with prompts, so called 3D-to-3D.🔥 We will soon reveal more features. Stay tuned!show more

From flat image to animated 3D models in Spaces... → Generate 3D models from an image or a prompt → Retexture, remesh, convert and UV unwrap on the canvas → Auto-rig your characters and apply animations → Snapshot any model into your image or video workflow Now on Magnificshow more

Stop juggling disconnected tools and random prompts. APOB AI... brings everything into one seamless creation pipeline: AI Influencer Generator, GPT Image 2.0 (Chat to Generate & Chat to Edit), and Seedance 2.0 (Image to Video Ultra S). From creating consistent AI characters to refining images and generating cinematic videos, every step is built to keep your workflow smooth and your results consistent. Build high-quality AI influencers faster with more control, less friction, and at scale.show more

Tripo P1.0 is live. Introducing Smart Mesh in Tripo... Studio — generate structured 3D meshes in ~2 seconds. ⚡ ~2s generation 🧠 Smart topology 🛠 Production-ready assets 🌍 Built for game pipelines, real-time rendering, web 3D tools, and scalable content production From prompt to usable mesh — almost instantly. Try it: #3DAI #3DCG #3dart #Triposhow more

Diffusion for virtual worlds: we've trained a new model... to create 3D objects from text. And it's 50x faster than any alternative. We made each of these cute characters in just one minute with Genmo's new text-to-3D model. Build your own world atshow more

the fact that i can take an image of... a room and turn it into a 3d model in one shot is actually insane this took like 30 seconds from image to 3d modelshow more

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)”show more

Today, we released Lyra 2.0, a framework for generating... persistent, explorable 3D worlds at scale, from NVIDIA Research. Generating large-scale, complex environments is difficult for AI models. Current models often “forget” what spaces look like and lose track of movement over time, causing objects to shift, blur, or appear inconsistent. This prevents them from creating the reliable 3D environments required for downstream simulations. Lyra 2.0 solves these issues by: ✅ Maintaining per-frame 3D geometry to retrieve past frames and establish spatial correspondences ✅ Using self-augmented training to correct its own temporal drifting. Lyra 2.0 turns an image into a 3D world you can walk through, look back, and drop a robot into for real-time rendering, simulation, and immersive applications. ➡️ Learn more: 📄 Read the paper:show more

Developers at groundbreaking start-ups like Alpha3D and BOOM Interactive... are making it possible to quickly and accurately convert 2D images into high-quality #3D models with #OpenUSD. Read more:show more

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.show more

.Tencent Hy HY-World 2.0 has landed,fully OPEN SOURCE !... We kept hearing the same thing: world models look great, but you can't use the output. So we made one you can, real 3D assets you can edit, rearrange, and ship into production. Prompt to engine-ready 3D. For real this time： ✨Directly outputs editable, production-ready 3D assets ✨Seamlessly plugs into existing game pipelines ✨Multimodal input: text, image, videos 🪄Character mode: freely explore streets, buildings, and open worlds with realistic physics, collisions, and no time limits 🔗GitHub:show more

Here is a preview of the new bang options... for our 3D customizable vtuber model! ✨ Not everyone can afford a high end 1:1 3D vtuber model. Which is why my sister and I are working so hard to provide a customizable 3D vtuber avatar with the same level of quality and tech!🩷show more

Discover the next evolution of efficient content creation with... Dreamina Seedance 2.0 Mini. Designed to deliver high-quality results while maximizing efficiency, this model is a powerful choice for teams looking to scale content production with ease. Whether you’re creating cinematic videos, marketing campaigns, or engaging short-form creator content, Seedance 2.0 Mini helps streamline workflows and boost productivity. Limited-Time Offer: Save up to 55% compared to Seedance 2.0. Try it here: Generate more. Spend less. Maintain exceptional quality. #Seedance2Mini #CapCutshow more

Another big drop from Hunyuan3D by Tencent. Hunyuan3D-Buffalo 1.0... is not just another text-to-3D model. The more interesting part is its approach to 3D understanding and editing. It can understand separate parts of a complete asset, extract them, remove or replace them with prompts, and edit only the selected region while keeping the rest of the geometry unchanged. That feels like a much more useful direction for 3D AI in general: not just generating a mesh once, but actually understanding its structure and letting you continue working with it. The model combines Qwen-VL, TRELLIS and Hunyuan3D, and was trained on an impressive dataset of 87 million 3D samples. Source:show more

Idea → stunning game in minutes with GPT Image... 2.0. Full pipeline for a human companion vs transformer scene: 1. GPT Image 2.0 -- character + scene concepts 2. Grok Imagine -- turn stills into video mockups or cutscenes 3. fal + MeshyAI -- generate the 3D assets 4. Rosebud -- port in as cutscenes or playable characters and vibe code the game Character design and game scene ideation is fundamentally different now. Reply for Rosebud credits to try implement this yourself. Full prompts for character sheets below 👇🎮show more

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 scene of New York featuring its most iconic landmarks and architectural elements. Use soft, refined textures with realistic PBR materials and gentle, lifelike lighting and shadows. Integrate the current weather conditions directly into the city environment to create an immersive atmospheric mood.Use a clean, minimalistic composition with a soft, solid-colored background. At the top-center, place the title "New York" in large bold text in white. You can create different effects by changing the city name according to your needs.show more