2D keypoint detection with Pytorch Lightning and wandb

Tensors, for human consumption

A latent text-to-image diffusion model

C++ implementation of Fast Depth Densification for Occlusion-aware Augmented Reality (SIGGRAPH-Asia 2018)

Tileable Stable Diffusion - Cog model

A collaboration friendly studio for NeRFs

[CVPR2020] f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation https://arxiv.org/abs/2001.10331

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image …

Convert Machine Learning Code Between Frameworks

🚴 Call stack profiler for Python. Shows you why your code is slow!

Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.

PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

The code of SCFusion: Real-time Incremental Scene Reconstruction with Semantic Completion

[ECCV 2020] Learning stereo from single images using monocular depth estimation networks

Project of Siggraph Asia 2020 paper: Scene Mover: Automatic Move Planning for Scene Arrangement by Deep Reinforcement Learning

Visual localization made easy with hloc

🤖🖌️ Generate photo-realistic textures based on source images or (soon) PBR materials. Remix, remake, mashup! Useful if you want to create variations on a theme or elaborate on an existing texture.

Code release for NeRF (Neural Radiance Fields)

Sandbox for training deep learning networks

This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"

[CVPR 2020] Estimation of the visible and hidden traversable space from a single color image

Deep Depth Completion of a Single RGB-D Image

Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"

Python library for creating flow networks and computing the maxflow/mincut (aka graph-cuts for Python)

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"

Deal with bad samples in your dataset dynamically, use Transforms as Filters, and more!