Voldemort108X's Stars
Significant-Gravitas/AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
microsoft/vscode
Visual Studio Code
facebookresearch/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.
google-research/google-research
Google Research
google-research/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
facebookresearch/dinov2
PyTorch code and models for the DINOv2 self-supervised learning method.
facebookresearch/xformers
Hackable and optimized Transformers building blocks, supporting a composable construction.
lucidrains/denoising-diffusion-pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
z-x-yang/Segment-and-Track-Anything
An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) for key-frame segmentation and Associating Objects with Transformers (AOT) for efficient tracking and propagation purposes.
VainF/Awesome-Anything
General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX
facebookresearch/ConvNeXt-V2
Code release for ConvNeXt V2 model
keyu-tian/SparK
[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling"
MedMNIST/MedMNIST
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
KMnP/vpt
❄️🔥 Visual Prompt Tuning [ECCV 2022] https://arxiv.org/abs/2203.12119
52CV/CVPR-2023-Papers
PruneTruong/DenseMatching
Dense matching library based on PyTorch
yoxu515/aot-benchmark
An efficient modular implementation of Associating Objects with Transformers for Video Object Segmentation in PyTorch
ranandalon/mtl
Unofficial implementation of: Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
PacktPublishing/Python-3-Object-Oriented-Programming-Third-Edition
Python 3 Object-Oriented Programming – Third Edition, published by Packt
hitachinsk/SAMed
The implementation of the technical report: "Customized Segment Anything Model for Medical Image Segmentation"
megvii-research/CVPR2023-DMVFN
CVPR2023 (highlight) - A Dynamic Multi-Scale Voxel Flow Network for Video Prediction
Verified-Intelligence/auto_LiRPA
auto_LiRPA: An Automatic Linear Relaxation based Perturbation Analysis Library for Neural Networks and General Computational Graphs
mattpoggi/mono-uncertainty
CVPR 2020 - On the uncertainty of self-supervised monocular depth estimation
pmorerio/dl-uncertainty
"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).
david-knigge/ccnn
Code repository of the paper "Modelling Long Range Dependencies in ND: From Task-Specific to a General Purpose CNN" https://arxiv.org/abs/2301.10540.
coolbeam/UPFlow_pytorch
PyTorch implementation of UPFlow (unsupervised optical flow learning)
abdo-eldesokey/pncnn
The official PyTorch implementation for "Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End"
ShellingFord221/My-implementation-of-What-Uncertainties-Do-We-Need-in-Bayesian-Deep-Learning-for-Computer-Vision
Pytorch implementation of classification task in What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision (simple version)
martius-lab/beta-nll
beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022
jgdo/uflow_pytorch
Python implementation of https://github.com/google-research/google-research/tree/master/uflow