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Found 14 papers, 5 papers with code
Dynamic Inference With Grounding Based Vision and Language Models
For example, recent image and language models with more than 200M parameters have been proposed to learn visual grounding in the pre-training step and show impressive results on downstream vision and language tasks.
Adversarial Machine Learning Attacks Against Video Anomaly Detection Systems
We demonstrate how Wi-Fi deauthentication attack, a notoriously easy-to-perform and effective denial-of-service (DoS) attack, can be utilized to generate adversarial data for video anomaly detection systems.
End-to-End Semantic Video Transformer for Zero-Shot Action Recognition
While video action recognition has been an active area of research for several years, zero-shot action recognition has only recently started gaining traction.
TiSAT: Time Series Anomaly Transformer
While anomaly detection in time series has been an active area of research for several years, most recent approaches employ an inadequate evaluation criterion leading to an inflated F1 score.
Rethinking Video Anomaly Detection - A Continual Learning Approach
The experimental results show that the existing state-of-the-art methods are not suitable for the considered practical challenges, and the proposed algorithm outperforms them with a large margin in continual learning and few-shot learning tasks
An Efficient Approach for Anomaly Detection in Traffic Videos
We also propose a sequential change detection algorithm that can quickly adapt to a new scene and detect changes in the similarity statistic.
A Modular and Unified Framework for Detecting and Localizing Video Anomalies
Anomaly detection in videos has been attracting an increasing amount of attention.
Road Damage Detection using Deep Ensemble Learning
Road damage detection is critical for the maintenance of a road, which traditionally has been performed using expensive high-performance sensors.
Online Anomaly Detection in Surveillance Videos with Asymptotic Bounds on False Alarm Rate
Motivated by these research gaps, we propose an online anomaly detection method in surveillance videos with asymptotic bounds on the false alarm rate, which in turn provides a clear procedure for selecting a proper decision threshold that satisfies the desired false alarm rate.
Fast Unsupervised Anomaly Detection in Traffic Videos
In this paper, we propose a fast unsupervised anomaly detection system comprising of three modules: preprocessing module, candidate selection module and backtracking anomaly detection module.
Timely Detection and Mitigation of Stealthy DDoS Attacks via IoT Networks
Internet of Things (IoT) networks consist of sensors, actuators, mobile and wearable devices that can connect to the Internet.
Continual Learning for Anomaly Detection in Surveillance Videos
Anomaly detection in surveillance videos has been recently gaining attention.
Anomaly Detection In Surveillance Videos
Continual Learning
+2
Any-Shot Sequential Anomaly Detection in Surveillance Videos
Even though the performance of state-of-the-art methods on publicly available data sets has been competitive, they demand a massive amount of training data.
Ranked #21 on
Anomaly Detection
on ShanghaiTech
Synthetic Image Augmentation for Improved Classification using Generative Adversarial Networks
Object detection and recognition has been an ongoing research topic for a long time in the field of computer vision.
