Semantic Segmentation Architectures Implemented in PyTorch
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DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral
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Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions"
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Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet
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A high-performance distributed training framework for Reinforcement Learning
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PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
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OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
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FedML - The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated learning, cross-device federated learning on smartphones/IoTs, and research simulation. MLOps and App Marketplace are also enabled (https://open.fedml.ai).
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Modularized Implementation of Deep RL Algorithms in PyTorch
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Rust bindings for the C++ api of PyTorch.
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🏅 Collection of Kaggle Solutions and Ideas 🏅
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Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
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Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
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Time series forecasting with PyTorch
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Deep-reinforcement-learning-with-pytorchby sweetice
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PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
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Massively Parallel Deep Reinforcement Learning. 🔥
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An optimizer that trains as fast as Adam and as good as SGD.
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A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
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A deep learning library for video understanding research.
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A Simple and Versatile Framework for Object Detection and Instance Recognition
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Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.
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PyTorch implementation of Super SloMo by Jiang et al.
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The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
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Code repository for the examples from the Packt book "Learning Threejs"
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LPIPS metric. pip install lpips
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Python 
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Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
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CUDA Templates for Linear Algebra Subroutines
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Deep recommender models using PyTorch.
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Siamese and triplet networks with online pair/triplet mining in PyTorch
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High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
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a distributed deep learning platform
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pytorch tutorial for beginners
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腾讯优图高精度双分支人脸检测器
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A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
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Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
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Sandbox for training deep learning networks
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The project is an official implement of our ECCV2018 paper "Simple Baselines for Human Pose Estimation and Tracking(https://arxiv.org/abs/1804.06208)"
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a-PyTorch-Tutorial-to-Object-Detectionby sgrvinod
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2785
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SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
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rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.
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Visual tracking library based on PyTorch.
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PyTorch original implementation of Cross-lingual Language Model Pretraining.
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Graph Attention Networks (https://arxiv.org/abs/1710.10903)
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An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.
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Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
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pytorch-semsegby meetshah1995
Semantic Segmentation Architectures Implemented in PyTorch
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3054
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MiDaSby isl-org
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"
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3028
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RepVGGby DingXiaoH
RepVGG: Making VGG-style ConvNets Great Again
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3023
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visslby facebookresearch
VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.
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3023
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generative_inpaintingby JiahuiYu
DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral
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3018
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practicalAI-cnby MLEveryday
AI实战-practicalAI 中文版
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glowby openai
Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions"
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3014
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tencent-ml-imagesby Tencent
Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet
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3010
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PARLby PaddlePaddle
A high-performance distributed training framework for Reinforcement Learning
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3000
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RL-Adventure-2by higgsfield
PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
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2994
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fast-reidby JDAI-CV
SOTA Re-identification Methods and Toolbox
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2970
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mmtrackingby open-mmlab
OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
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2968
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FedMLby FedML-AI
FedML - The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated learning, cross-device federated learning on smartphones/IoTs, and research simulation. MLOps and App Marketplace are also enabled (https://open.fedml.ai).
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2950
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DeepRLby ShangtongZhang
Modularized Implementation of Deep RL Algorithms in PyTorch
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2938
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EASTby argman
A tensorflow implementation of EAST text detector
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2937
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tch-rsby LaurentMazare
Rust bindings for the C++ api of PyTorch.
Rust
2930
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kaggle-solutionsby faridrashidi
🏅 Collection of Kaggle Solutions and Ideas 🏅
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DeepNLP-models-Pytorchby DSKSD
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
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2916
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flownet2-pytorchby NVIDIA
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
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2915
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pytorch-forecastingby jdb78
Time series forecasting with PyTorch
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2908
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Deep-reinforcement-learning-with-pytorchby sweetice
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
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2907
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ElegantRLby AI4Finance-Foundation
Massively Parallel Deep Reinforcement Learning. 🔥
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2902
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AdaBoundby Luolc
An optimizer that trains as fast as Adam and as good as SGD.
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2898
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nlp-architectby IntelLabs
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
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2897
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pytorchvideoby facebookresearch
A deep learning library for video understanding research.
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2894
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simpledetby TuSimple
A Simple and Versatile Framework for Object Detection and Instance Recognition
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2892
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BasicSRby xinntao
Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.
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2890
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Super-SloMoby avinashpaliwal
PyTorch implementation of Super SloMo by Jiang et al.
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2881
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HRNet-Semantic-Segmentationby HRNet
The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
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2879
Updated: 2 y ago
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learning-threejsby josdirksen
Code repository for the examples from the Packt book "Learning Threejs"
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2878
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PerceptualSimilarityby richzhang
LPIPS metric. pip install lpips
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2877
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Image-Super-Resolution-via-Iterative-Refinementby Janspiry
Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
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2865
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cutlassby NVIDIA
CUDA Templates for Linear Algebra Subroutines
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2862
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spotlightby maciejkula
Deep recommender models using PyTorch.
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2858
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siamese-tripletby adambielski
Siamese and triplet networks with online pair/triplet mining in PyTorch
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2855
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cleanrlby vwxyzjn
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
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2846
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singaby apache
a distributed deep learning platform
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2832
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pytorch-beginnerby L1aoXingyu
pytorch tutorial for beginners
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2829
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FaceDetection-DSFDby Tencent
腾讯优图高精度双分支人脸检测器
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2823
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Detectron.pytorchby roytseng-tw
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
Python
2817
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jittorby Jittor
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
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2816
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imgclsmobby osmr
Sandbox for training deep learning networks
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2796
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human-pose-estimation.pytorchby microsoft
The project is an official implement of our ECCV2018 paper "Simple Baselines for Human Pose Estimation and Tracking(https://arxiv.org/abs/1804.06208)"
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2786
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a-PyTorch-Tutorial-to-Object-Detectionby sgrvinod
SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
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2785
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rllabby rll
rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.
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2784
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pytrackingby visionml
Visual tracking library based on PyTorch.
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2778
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XLMby facebookresearch
PyTorch original implementation of Cross-lingual Language Model Pretraining.
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2767
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GATby PetarV-
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
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2755
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PocketFlowby Tencent
An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.
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2754
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deep-learning-bookby rasbt
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
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