113 Open source projects that are alternatives of or similar to flowattack

TOFlow: Video Enhancement with Task-Oriented Flow

High-performance multiple object tracking based on YOLO, Deep SORT, and optical flow

(ECCV 2020) RANSAC-Flow: generic two-stage image alignment

Unsupervised Learning of Multi-Frame Optical Flow with Occlusions

Cool Vision projects

The main abnormal behaviors that this project can detect are: Violence, covering camera, Choking, lying down, Running, Motion in restricted areas. It provides much flexibility by allowing users to choose the abnormal behaviors they want to be detected and keeps track of every abnormal event to be reviewed. We used three methods to detect abnorma…

Google Colab notebook for running Nvidia flownet2-pytorch

BriefMatch real-time GPU optical flow

No description or website provided.

PWC-Network with TensorFlow

Multi-stream CNN architectures for action detection with actor-centric filtering

Visual odometry using optical flow and neural networks

Fork and OpenCV wrapper of the optical flow I/O and visualization code provided as part of the Sintel dataset [1].

A method about optimizing the facial landmark detection based on Kalman Filter, Optical Flow and Dlib

Shallow Optical Flow Three-Stream CNN For Macro and Micro-Expression Spotting From Long Videos

CUDA implementation of the paper "Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow" in CVPR 2014.

Compute dense optical flow using TV-L1 algorithm with NVIDIA GPU acceleration.

Vision-based Robot 3D Pose and Velocities Estimations

Face Detection and tracking using CamShift, Kalman Filter, Optical Flow

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM.

ROS package for Correlation Flow (ICRA 2018)

Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence, CVPR 2019

TensorFlow implementation for "Guided Optical Flow Learning"

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

Data augmentation for NLP

[EMNLP 2020] "T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack" by Boxin Wang, Hengzhi Pei, Boyuan Pan, Qian Chen, Shuohang Wang, Bo Li

Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]

Code for the paper "Addressing Model Vulnerability to Distributional Shifts over Image Transformation Sets", ICCV 2019

Paper list of Adversarial Examples

Python tools for analyzing the robustness properties of neural networks (NNs) from MIT ACL

Adversarial Ranking Attack and Defense, ECCV, 2020.

Robust Out-of-distribution Detection in Neural Networks

Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"

Source code and dataset for the CCKS201 paper "On Robustness and Bias Analysis of BERT-based Relation Extraction"

Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".

Reimplementing cool papers in PyTorch...

[CVPR 2022] S-attack library. Official implementation of two papers "Vehicle trajectory prediction works, but not everywhere" and "Are socially-aware trajectory prediction models really socially-aware?".

No.2 solution of Tianchi ImageNet Adversarial Attack Challenge.

Adversarial Attacks on Deep Neural Networks for Time Series Classification

This is a collection of algorithms and approaches used in the book adversarial deep learning

"GAN 인 액션"(한빛미디어, 2020)의 코드 저장소입니다.

Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-…

Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

A pytorch implementation of "Towards Deep Learning Models Resistant to Adversarial Attacks"

Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"

[ICCV2021 Oral] Fooling LiDAR by Attacking GPS Trajectory

Task-agnostic universal black-box attacks on computer vision neural network via procedural noise (CCS'19)

TrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses) of image classification in deep learning.

CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.

Natural Language Attacks in a Hard Label Black Box Setting.

KitanaQA: Adversarial training and data augmentation for neural question-answering models