📢MeshPad: Interactive Sketch-Conditioned Artist-Designed Mesh Generation and Editing📢 Users... can interactively design 3D models just from a sketch-based interface - check out the demo :) We break down the design process into addition with an autoregressive generator and deletion operations enabled by a classifier. To speed-up predictions, we propose a mesh-specific speculator such that users get immediate within a few seconds. Project: Video: Great work by Haoxuan Li Ziya Erkoç Lei Li Daniele Sirigatti V. Rosov Angela Daishow more

A GeoNode-based stylized cloud generator that lets you design... clouds as easily as editing any mesh. 👉 #b3dshow more

Garment3DGen 3D Garment Stylization and Texture Generation We introduce... Garment3DGen a new method to synthesize 3D garment assets from a base mesh given a single input image as guidance. Our proposed approach allows users to generate 3D textured clothes based on bothshow more

Many drugs work by binding to a specific target... in the body and blocking or changing what it does. An important first step in the drug development process is designing a molecule that can bind tightly to its target. Traditionally, that's meant weeks or months of expert work per target, sifting through a large number of candidates to identify the few that work. We wanted to test if Claude could successfully design novel protein binders from scratch (also called de novo design). With a protein design prompt written by a human expert, Claude autonomously designed protein binders against 14 out of 15 targets. We then worked with Adaptyv Bio and Twist Bioscience, who independently built and tested the proteins Claude designed.show more

Can we use motion to prompt diffusion models? Our... #ICLR2024 paper does just that. We propose Motion Guidance, a technique that allows users to edit an image by specifying “where things should move.”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

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.show more

📢GeomHair: Reconstruction of Hair Strands from Colorless 3D Scans📢... We present a novel method to reconstruct hair strands from colorless 3D scans by extracting orientation cues directly from the mesh surface geometry by finding local characteristic lines and from shaded renderings using a neural 2D line detector. We enhance the reconstruction with a diffusion prior trained on synthetic hair data and adapted to each scan using a tailored text prompt, allowing us to recover both simple and complex hairstyles without relying on color input. To support further research, we also introduce Strands400, the largest publicly available dataset of 3D hair strand reconstructions from real-world scans of 400 different people, featuring complicated hairstyles, such as ponytails and buns. 🌍 📷 Great work by Rachmadio Noval L. Artem Sevastopolsky Egor Zakharov @ness_prisshow more

The context size of video world models is only... a few frames. Like a human with severe memory loss! We design a long-term memory for world models based on explicit 3D representations inspired by the human mind. This enables long-term consistency. 1/3show more

Introducing pixelSplat: feed-forward Gaussian splats from image pairs! Led... by David Charatan and Lester Li, collaborating with Andrea Tagliasacchi! We propose a memory-efficient, fast and editable alternative to pixelNeRF based on 3D Gaussian Splatting! 1/nshow more

A few seconds from prompt to video — that's... faster than Twitch streams live. H3 Max on MiniMax Design, post-trained by fal. The speed-and-cost combo is what really stands out. You can iterate in seconds, not minutes.show more

GOOGLE 🔥: Interactive Reports are being prepared for the... upcoming release in Gemini Notebook. > New: You can now create interactive reports. > An interactive report with embedded Studio content. Users can customize these reports by providing a custom prompt and selecting a language. Based on the suggested prompt, this feature lets users generate interactive reports, user research reports, and complex visualizations. * Not available to the public yet.show more

🤗Another breakdown from an older project made for Lands... of Noara . It was one of my first 2D VFX on a shot and a great project to direct and work on. I also made the motion design. Animated by the fantastic Makadam #blender #animation #3D #p2designshow more

📢Introducing Generated Reality📢 A world model for XR that... turns your tracked hand and head poses into an interactive, generative video experience. Take world models to the next level by interacting with the world using your own body! 🔗 1/4show more

LI.​FI is live on Stellar. Apps and wallets building... with LI.​FI can now enable swaps and cross-chain transfers to and from Stellar through one integration. Making it easier for users and capital to move into the Stellar ecosystem. Powered by LI.​FI.show more

This was just a sketch from a few weeks... ago, but I suddenly got inspired and ended up polishing and editing it 😔show more

(1/n) 🚀 With FastVideo, you can now generate a... 5-second video in 5 seconds on a single H200 GPU! Introducing FastWan series, a family of fast video generation models trained via a new recipe we term as “sparse distillation”, to speed up video denoising time by 70X! 🖥️ Live demo: (Thanks to @gmicloud for the support!) 🔗 Blog: 🔓 We fully open-source our models, code, and data with Apache-2.0 licensesshow more

3DGS render blender add-on v3.0 ( was just open-sourced!... With KIRI tools, you can use "3DGS to mesh" function to get a mesh from Gaussian splatting, and now you can convert the mesh back to Gaussian splatting. It's kind of ironic, but we just try to bring handy tools to everyone. #GaussianSplatting #Blendershow more

🎥 Video Generation Using the Veo 3.1 Model! The... Veo 3.1 Video Generator Tool allows users to generate videos leveraging the Veo 3.1 model. It offers a streamlined experience designed for clarity, speed, and practical creative workflows. 🔗show more

Competition 2: Mesh Generation 🦾 Until now, our subnet... has focused on Gaussian splats. That work led to integrations with Unity, building the world’s largest 3D dataset, and early application deployments with real users and organic traffic growth. 🕹️ The next step is clear. Developers want native mesh generation that drops straight into existing game pipelines and unlocks real production use today. 🤖 Our competition format lets us move flexibly between goals, optimizing for near term commercial utility with meshes and balancing longer term research with Gaussian splat world models and digital twins. 📈 With significant open source mesh models releasing in the past weeks, the timing is right and the bar for miner innovation has never been higher. Mesh competition launches in 2 weeks!show more

Agentic UI interface product design is so much fun.... Recently, we are working with one of the companies who got funded $25M. We are researching their product and working out how Agentic features will help their users, with around 80-90% time saved by Agents’ feature. Investors love the idea so much. Can't wait to share the work. Hopefully, in the future, we can. We are helping them on UX, design system, redesigning the product, and so much more.show more