yugaoxiang324

fscan

一款内网综合扫描工具，方便一键自动化、全方位漏扫扫描。

MMOCR_tutorials

Jupyter notebook tutorials for MMOCR

mscnn

mscnn crowd counting model implementation, source from "Multi-scale Convolution Neural Networks for Crowd Counting" write by Zeng L, Xu X, Cai B, et al.

yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

ElectronBot

IIM

PyTorch implementations of the paper: "Learning Independent Instance Maps for Crowd Localization"

FIDTM

[IEEE TMM 23] Focal Inverse Distance Transform Maps for Crowd Localization

Urban-Sound-Classification

Urban sound classification using Deep Learning

mmocr

OpenMMLab Text Detection, Recognition and Understanding Toolbox

EndNote_Tutorial_Hand_by_Hand

手把手教你使用 EndNote X9/NoteExpress

CSP

High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection, CVPR, 2019

Pedestron

[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021

copy-paste-aug

Copy-paste augmentation for segmentation and detection tasks

detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

Detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

mmdetection

OpenMMLab Detection Toolbox and Benchmark

iterdet

[S+SSPR2020] IterDet: Iterative Scheme for Object Detection in Crowded Environments

neuralbody

Code for "Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans" CVPR 2021 best paper candidate

repulsion_loss_ssd

Repulsion Loss: Detecting Pedestrians in a Crowd. https://arxiv.org/abs/1711.07752

cascade-rcnn_Pytorch

An implementation of Cascade R-CNN: Delving into High Quality Object Detection.

Virus-School

Unity模拟病毒在校园中传播

Computer-simulation-of-virus-spread

使用Python创建了一个病毒在人群中传播的计算机仿真模型

shadowsocks-rss

ShadowsocksR update rss, SSR organization https://github.com/shadowsocksr

crowd-counting-scnn

This project is an implementation of the crowd counting model proposed in our CVPR 2017 paper - Switching Convolutional Neural Network(SCNN) for Crowd Counting. SCNN is an adaptation of the fully-convolutional neural network and uses an expert CNN that chooses the best crowd density CNN regressor for parts of the scene from a bag of regressors. This helps it tackle intra-scene crowd density variation and obtain SOTA results

Awesome-Crowd-Counting

Awesome Crowd Counting

SR-LSTM

States Refinement LSTM

CrowdFlow

Optical Flow Dataset and Benchmark for Visual Crowd Analysis

CrowdNav

[ICRA19] Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

Multi-Human-Parsing

🔥🔥Official Repository for Multi-Human-Parsing (MHP)🔥🔥

SCNet

The official PyTorch implementation of CVPR 2020 paper "Improving Convolutional Networks with Self-Calibrated Convolutions"