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autoencoders

bayesianphdcourse

Exercise solutions to Bayesian statistics, simulation and software (2016)

computer_vision_samples

deep-learning-course

deep_learning_samples

deepstream_dockers

A project demonstrating how to make DeepStream docker images.

diffusion-point-cloud

:thought_balloon: Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)

dift

[NeurIPS'23] Emergent Correspondence from Image Diffusion

dockers

A collection of dockerfiles and scripts

ffcv

FFCV: Fast Forward Computer Vision (and other ML workloads!)

geoseg

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery, ISPRS. Also, including other vision transformers and CNNs for satellite, aerial image and UAV image segmentation.

gpu_monitoring

Monitoring computers/GPU usage

graph-neural-networks

harbor-image-data-extraction

Extract Images from the Video Clip data and the metadata

imagen-pytorch

Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch

keypoint-detection

2D keypoint detection with Pytorch Lightning and wandb

kinect2grabber

Simple and extendable command-line application to acquire frames from Microsoft Kinect v2 and optionally store them. Visualization is performed with OpenCV.

kinectgrabber

Grabber of Point Cloud Library based on Kinect for Windows SDK

latent-diffusion

High-Resolution Image Synthesis with Latent Diffusion Models

latent_3d_points

Auto-encoding & Generating 3D Point-Clouds.

libfreenect2pclgrabber

a grabber for the kinect2 which returns a registered pcl point cloud

mae

PyTorch implementation of Masked Autoencoder

mae-pytorch

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

markpp.github.io

Blog, on a PhD in robotics, based on Pelican.

midas

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"

object-detection

This is an ongoing project of designing a custom object detector from scratch. You can also use the pytorch-lightning training pipeline to train your own model.

object_detectors

paper-notes

pl_bolts

Pytorch Lightning implementations of different deep learning model along with various data modules

point-cloud-exercises

Exercises for Point Cloud lecture