amiormu

amiormu's Stars

• ossrs/srs

  SRS is a simple, high-efficiency, real-time media server supporting RTMP, WebRTC, HLS, HTTP-FLV, HTTP-TS, SRT, MPEG-DASH, and GB28181.

  Language:C++26.2k8391.5k5.4k

• junyanz/pytorch-CycleGAN-and-pix2pix

  Image-to-Image Translation in PyTorch

  Language:Python23.4k3481.5k6.4k

• CopyTranslator/CopyTranslator

  🔠Foreign language reading and translation assistant based on copy and translate.

  Language:TypeScript17.3k4175281.9k

• thunlp/GNNPapers

  Must-read papers on graph neural networks (GNN)

  16.2k598183k

• amusi/daily-paper-computer-vision

  记录每天整理的计算机视觉/深度学习/机器学习相关方向的论文

  6.4k425121.3k

• kuangliu/pytorch-cifar

  95.47% on CIFAR10 with PyTorch

  Language:Python6.1k951362.2k

• kenshohara/3D-ResNets-PyTorch

  3D ResNets for Action Recognition (CVPR 2018)

  Language:Python3.9k58269930

• JDAI-CV/fast-reid

  SOTA Re-identification Methods and Toolbox

  Language:Python3.5k60637844

• meetps/pytorch-semseg

  Semantic Segmentation Architectures Implemented in PyTorch

  Language:Python3.4k106222792

• commonsense/conceptnet5

  Code for building ConceptNet from raw data.

  Language:Roff2.8k174171355

• weslynn/AlphaTree-graphic-deep-neural-network

  AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN），图神经网络（GNN），NLP，大数据相关的发展路书(roadmap), 并附海量源码（python，pytorch）带大家消化基本知识点，突破面试，完成从新手到合格工程师的跨越，其中深度学习相关论文附有tensorflow caffe官方源码，应用部分含推荐算法和知识图谱

  2.8k1277601

• michuanhaohao/reid-strong-baseline

  Bag of Tricks and A Strong Baseline for Deep Person Re-identification

  Language:Python2.3k52218575

• Qidian213/deep_sort_yolov3

  Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow

  Language:Python1.7k44172591

• facebookarchive/C3D

  C3D is a modified version of BVLC caffe to support 3D ConvNets.

  Language:Jupyter Notebook1.2k54429508

• lightaime/deep_gcns_torch

  Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org

  Language:Python1.1k1760156

• facebookresearch/VMZ

  VMZ: Model Zoo for Video Modeling

  Language:Python1k109123158

• felixchenfy/Realtime-Action-Recognition

  Apply ML to the skeletons from OpenPose; 9 actions; multiple people. (WARNING: I'm sorry that this is only good for course demo, not for real world applications !!! Those ary very difficult !!!)

  Language:Python9042294261

• jeffreyyihuang/two-stream-action-recognition

  Using two stream architecture to implement a classic action recognition method on UCF101 dataset

  Language:Python8652281249

• jwyang/graph-rcnn.pytorch

  [ECCV 2018] Official code for "Graph R-CNN for Scene Graph Generation"

  Language:Python73429113157

• lshiwjx/2s-AGCN

  Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19

  Language:Python67112106181

• TianzhongSong/Real-Time-Action-Recognition

  Real-time pose estimation and action recognition

  Language:Python4091432126

• cagbal/ros_people_object_detection_tensorflow

  An extensive ROS toolbox for object detection & tracking and face/action recognition with 2D and 3D support which makes your Robot understand the environment

  Language:Python252172293

• ming71/DAL

  [AAAI 2021] Official implementation of "Dynamic Anchor Learning for Arbitrary-Oriented Object Detection".

  Language:Python22775438

• ChengeYang/Human-Pose-Estimation-Benchmarking-and-Action-Recognition

  Deep Learning Project.

  Language:Python22481566

• kevin-ssy/Optical-Flow-Guided-Feature

  Implementation Code of the paper Optical Flow Guided Feature, CVPR 2018

  Language:C++19613043

• cvlab-yonsei/projects

  Language:HTML9981320

• jiayan97/linknet-pytorch

  Pytorch reimplementation of LinkNet for Scene Graph Generation

  Language:Python28026

• Lornatang/PyTorch

  An open source deep learning platform that provides a seamless path from research prototyping to production deployment

  Language:Python172012

• dreamhomes/knowledge-graph-example

  构建简单的知识图谱实例——公司股票数据

  Language:Python8105

• haim-barad/action-recognition-compressed-domain

  Code for submission of Neurips 2019 paper entitled "Accelerating Action Recognition In The Compressed Domain"

  Language:Python7013