Pinned Repositories
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
object_detectors
markpp's Repositories
markpp/object_detectors
markpp/autoencoders
markpp/deep-learning-course
markpp/deepstream_dockers
A project demonstrating how to make DeepStream docker images.
markpp/diffusion-point-cloud
:thought_balloon: Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)
markpp/dift
[NeurIPS'23] Emergent Correspondence from Image Diffusion
markpp/dockers
A collection of dockerfiles and scripts
markpp/ffcv
FFCV: Fast Forward Computer Vision (and other ML workloads!)
markpp/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.
markpp/Graph-Neural-Networks
markpp/GPU_monitoring
Monitoring computers/GPU usage
markpp/imagen-pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch
markpp/keypoint-detection
2D keypoint detection with Pytorch Lightning and wandb
markpp/latent-diffusion
High-Resolution Image Synthesis with Latent Diffusion Models
markpp/MAE
PyTorch implementation of Masked Autoencoder
markpp/MAE-pytorch
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners
markpp/markpp.github.io
Blog, on a PhD in robotics, based on Pelican.
markpp/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"
markpp/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.
markpp/pl_bolts
Pytorch Lightning implementations of different deep learning model along with various data modules
markpp/point-cloud-exercises
Exercises for Point Cloud lecture
markpp/PoseFromPointClouds
Tensorflow and Pytorch implementations for pose predictions from point clouds.
markpp/poster-generator
Generating poter of freshly graduated PhD students from AAU Visual Analysis and Perception
markpp/ros2_deepstream
markpp/segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
markpp/segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
markpp/sewer_autoencoders
Autoencoder implementations for analysis of sewer inspection images
markpp/taming-transformers
Taming Transformers for High-Resolution Image Synthesis
markpp/thermal_autoencoder
markpp/torch2trt
An easy to use PyTorch to TensorRT converter