- Zurich, Switzerland
Stars
Code for the paper "Language Models are Unsupervised Multitask Learners"
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
[ECCV24] official code for "OGNI-DC: Robust Depth Completion with Optimization-Guided Neural Iterations"
Visual Odometry with Inertial and Depth (VOID) dataset
Video+code lecture on building nanoGPT from scratch
Implementation of our paper 'Bilateral Propagation Network for Depth Completion'
[CVPR 2023] Official repository for downloading, processing, visualizing, and training models on the ARCTIC dataset.
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
State-of-the-Art Text Embeddings
Schedule-Free Optimization in PyTorch
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
[CVPR 2024 - Oral, Best Paper Award Candidate] Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
A python library for self-supervised learning on images.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.