438 Open source projects that are alternatives of or similar to Anomaly Detection In Surveillance Videos

[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Combine Baidu Research warpctc with Caffe

MobileNet-SSD(MobileNetSSD) + Neural Compute Stick(NCS) Faster than YoloV2 + Explosion speed by RaspberryPi · Multiple moving object detection with high accuracy.

YOLO V2 & V3 , YOLO Combined with RCNN and MaskRCNN

Foremast adds application resiliency to Kubernetes by leveraging machine learnt patterns of application health to keep applications healthy and stable

Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)

📹 一个短视频APP视频内容安全审核的思路调研及实现汇总

Data-parallel image stylization using Caffe.

vehicle image retrieval using k CNNs ensemble method

Dockerfile and runscripts for DispNet and FlowNet1 (estimation of disparity and optical flow)

Caffe and Python implementation of Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

Reimplementation ResNet on cifar10 with caffe

Reference caffe implementation of LSUV initialization

Noise-Tolerant Paradigm for Training Face Recognition CNNs

CORe50: a new Dataset and Benchmark for Continual Learning

A high-level machine learning and deep learning library for the PHP language.

This is an implematation project of face detection and recognition. The face detection using MTCNN algorithm, and recognition using LightenenCNN algorithm.

《深度学习与计算机视觉》配套代码

开源人脸口罩检测模型和数据 Detect faces and determine whether people are wearing mask.

Caffe Implementation of Google's MobileNets (v1 and v2)

Convert darknet weights to caffemodel

train resnet on imagenet from scratch with caffe

Find big moving stocks before they move using machine learning and anomaly detection

Time series based anomaly detector

CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)

PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume, CVPR 2018 (Oral)

A curated list of awesome anomaly detection resources

BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics

Trajectory-pooled Deep-Convolutional Descriptors

Trojan Attack on Neural Network

A Computation Graph Virtual Machine Based Deep Learning Framework

Dockerfile and runscripts for FlowNet 2.0 (estimation of optical flow)

MobileNet-v2 experimental network description for caffe

Deep Learning Benchmarking Suite

Implementation of Visual Feature Attribution using Wasserstein GANs (VAGANs, https://arxiv.org/abs/1711.08998) in PyTorch

Log-based Impactful Problem Identification using Machine Learning [FSE'18]

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

Deep Learning sample programs using PyTorch in C++

Caffe models (including classification, detection and segmentation) and deploy files for famouse networks

Add-on package for ONNX format support in Chainer

Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17.

Kibana Alert & Report App for Elasticsearch

A robust, and flexible open source User & Entity Behavior Analytics (UEBA) framework used for Security Analytics. Developed with luv by Data Scientists & Security Analysts from the Cyber Security Industry. [PRE-ALPHA]

TensorRT Net Wrapper

Source code for Skip-GANomaly paper

Some tools and examples for pyCaffe including LMDB I/O, custom Python layers and monitoring training error and loss.

AI on Hadoop

Transform the caffe model to pytorch model for Temporal Segment Network

Kaggle dogs vs cats solution in Caffe

face detection and alignment with mtcnn

SeqFace : Making full use of sequence information for face recognition

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

A Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.

Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. In CVPR, 2017.

List of tools & datasets for anomaly detection on time-series data.

log anomaly detection toolkit including DeepLog

Caffe implementation of "Fast and Accurate Single Image Super-Resolution via Information Distillation Network" (CVPR 2018)