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

Introducing 📦𝗔𝗿𝘁𝗶𝗟𝗮𝘁𝗲𝗻𝘁🔧 (SIGGRAPH Asia 2025) — a high-quality 3D... diffusion model that explicitly models object articulation, paving the way for richer, more realistic assets in embodied AI and simulation: – Generates fully articulated 3D objects – Physically plausible joints & motion – High-fidelity 3D Gaussian appearance – Supports generation from a single real image arXiv: Project: Code (coming soon):show more

Check out TriPlaneNet! From a single image, we predict... EG3D latents & offsets, thus obtaining high-fidelity 3D models. Works in real time! Great work by our stellar MA student Ananta R. Bhattarai advised by Artem Sevastopolsky #WACV2024show more

Here’s how to create this cool 3D scene from... a single image! 📸 Midjourney (isometric image generation) Trellis (Image to 3D Gaussian Splat) Browser Lab (3D Editor Splat Import)show more

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 #geowizardshow 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

🚀 Introducing GenLit – Reformulating Single-Image Relighting as Video... Generation! We leverage video diffusion models to perform realistic near-field relighting from just a single image—No explicit 3D reconstruction or ray tracing required! No intermediate graphics buffers, directly in the pixel space! 📄 Dive into the paper: 🎥 Project page & demos: 🛠 Code coming soon! #GenerativeAI #ComputerVision #Relighting #DiffusionModels #Graphics 🧵 1/5show more

🤯 𝐒𝐥𝐢𝐜𝐞𝐝𝐢𝐭 : A revolutionary approach to zero-shot video... editing✏️🎥 using text-to-image diffusion models 🎞️Slicedit achieves great temporal consistency by leveraging spatio-temporal "slices"🔀show more

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

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

(1/2) 📢𝐍𝐏𝐆𝐀: 𝐍𝐞𝐮𝐫𝐚𝐥 𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐫𝐢𝐜 𝐆𝐚𝐮𝐬𝐬𝐢𝐚𝐧 𝐀𝐯𝐚𝐭𝐚𝐫𝐬 📢 #SIGGRAPHAsia We... leverage a neural parametric representation to facilitate precise control over 3D Gaussians to obtain high-fidelity avatars.show more

DreamCraft3D++ can generate animatable high-quality 3D assets from an... image in 10 minutes! Yes, it supports meshes 🔥 Links ⬇️show more

Spell AI making a 3d volume from a single... image. Link belowshow more

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 ⬇️show more

🆕 🔥 AniDoc: Animation Creation Made Easier It can... colorize a sequence of sketches based on a character design reference with high fidelity, even when the sketches significantly differ in pose and scale. Explore more ⬇️show more

HOLY SHIT - generate 3D mesh from a single... image in LESS THAN A SECOND 🤯show more

Artificial Analysis Image-to-video generation is just as impressive. Input... image: "Generate a 16:9 image from a dashcam view of a formula 1 racing event" Video prompt: "A high-speed racing event where a car navigates multiple winding turns" 🔊 Sound on - generated by Cosmos 3.show more