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MPI-IS
- Munich, Germany
- https://zielon.github.io/
- @w_zielonka
Highlights
- Pro
Stars
[CVPR 2025] InteractVLM: 3D Interaction Reasoning from 2D Foundational Models
A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation masks, depth maps, and optical flow.
PARC: Physics-based Augmentation with Reinforcement Learning for Character Controllers
Cosmos-Transfer1-DiffusionRenderer: High-quality video de-lighting and re-lighting based on Cosmos video diffusion framework
[Official Code] Pixel3DMM: Versatile Screen-Space Priors for Single-Image 3D Face Reconstruction
Code for SIGGRAPH2024 paper "ContourCraft: Learning to Resolve Intersections in Neural Multi-Garment Simulations"
[SIGGRAPH ASIA '24] GGHead: Fast and Generalizable 3D Gaussian Heads
Unified framework for robot learning built on NVIDIA Isaac Sim
CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control
Code for our CVPR'25 paper - "DiffLocks: Generating 3D Hair from a Single Image using Diffusion Models"
Official inference framework for 1-bit LLMs
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
Original reference implementation of "EVER: Exact Volumetric Ellipsoid Rendering for Real-time View Synthesis"
Ray tracing and hybrid rasterization of Gaussian particles
[SIGGRAPH 2025] Diffusion as Shader: 3D-aware Video Diffusion for Versatile Video Generation Control
Wan: Open and Advanced Large-Scale Video Generative Models
A 3D Gaussian Splatting framework with various derived algorithms and an interactive web viewer
Official repo for paper "Structured 3D Latents for Scalable and Versatile 3D Generation" (CVPR'25 Spotlight).
Code for paper "Gaussian Garments: Reconstructing Simulation-Ready Clothing with Photo-Realistic Appearance from Multi-View Video"
GEM - Gaussian Eigen Models for Human Heads [CVPR 2025]
[CVPR 2025 Best Paper Award] VGGT: Visual Geometry Grounded Transformer
[ICML'23] StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis