NoPlenty

NoPlenty's Stars

• henrryzh1/UR-DMU

  Official code for AAAI2023 paper "Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection"

  Language:Python604

• Tushar-N/pytorch-resnet3d

  I3D Nonlocal ResNets in Pytorch

  Language:Python24539

• SwinTransformer/Video-Swin-Transformer

  This is an official implementation for "Video Swin Transformers".

  Language:Python1.4k196

• nutuniv/SSRL

  Language:Python181

• louisYen/S3R

  video anomaly detection

  Language:Python7612

• Roc-Ng/XDVioDet

  Official implementation of "Not only Look, but also Listen: Learning Multimodal Violence Detection under Weak Supervision" ECCV2020

  Language:Python10117

• jlezama/OrthogonalLowrankEmbedding

  Language:C++6215

• mpc001/Lipreading_using_Temporal_Convolutional_Networks

  ICASSP'22 Training Strategies for Improved Lip-Reading; ICASSP'21 Towards Practical Lipreading with Distilled and Efficient Models; ICASSP'20 Lipreading using Temporal Convolutional Networks

  Language:Python380102

• elliottzheng/CopyTranslator

  The Project had moved to elsewhere. Please go to|项目已迁移至别处，请到

  Language:Python951154

• ktr-hubrt/MPN

  Official codes of CVPR21 paper: Learning Normal Dynamics in Videos with Meta Prototype Network

  Language:Python12643

• DavideA/c3d-pytorch

  Pytorch porting of C3D network, with Sports1M weights

  Language:Python34280

• wanboyang/anomly_feature.pytorch

  Language:Python296

• GowthamGottimukkala/I3D_Feature_Extraction_resnet

  I3D features extractor with resnet50 backbone

  Language:Python6216

• zergtant/pytorch-handbook

  pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

  Language:Jupyter Notebook20.1k5.4k

• fjchange/MIST_VAD

  Official codes for CVPR2021 paper "MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection"

  Language:Python12627

• StevenLiuWen/ano_pred_cvpr2018

  Official implementation of Paper Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018

  Language:Python435126

• qijiezhao/pseudo-3d-pytorch

  pytorch version of pseudo-3d-residual-networks(P-3D), pretrained model is supported

  Language:Python451113

• behnazak/Vigil-007SourceCode

  Language:Matlab165

• jx-zhong-for-academic-purpose/GCN-Anomaly-Detection

  Source codes of our paper in CVPR 2019: Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection

  Language:Python23143

• ktr-hubrt/WSAL

  Official codes for paper: Localizing Anomalies from Weakly-Labeled Videos

  Language:Python739

• wanboyang/Anomaly_AR_Net_ICME_2020

  This repository is for Weakly Supervised Video Anomaly Detection via Center-Guided Discriminative Learning(ICME 2020). The original paper can be found (https://ieeexplore.ieee.org/document/9102722) or (https://arxiv.org/abs/2104.07268)

  Language:Python518

• xaggi/claws_eccv

  Project page for the 'CLAWS: Clustering Assisted Weakly Supervised Learning with Normalcy Suppression for Anomalous Event Detection', ECCV 2020 paper.

  124

• tianyu0207/RTFM

  Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]

  Language:Python32177

• fjchange/awesome-video-anomaly-detection

  Papers for Video Anomaly Detection, released codes collection, Performance Comparision.

  581101

• hoya012/awesome-anomaly-detection

  A curated list of awesome anomaly detection resources

  2.7k513

• yzhao062/pyod

  A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

  Language:Python8.4k1.4k

• fengdu78/Coursera-ML-AndrewNg-Notes

  吴恩达老师的机器学习课程个人笔记

  Language:HTML31.5k10.6k

• cvlab-yonsei/MNAD

  An official implementation of "Learning Memory-guided Normality for Anomaly Detection" (CVPR 2020) in PyTorch.

  Language:Python33482

• yzhao062/anomaly-detection-resources

  Anomaly detection related books, papers, videos, and toolboxes

  Language:Python8.2k1.7k

• datawhalechina/pumpkin-book

  《机器学习》（西瓜书）公式详解

  23.8k4.7k