Nov 19, 2021 · We elaborately design a video prediction network with appearance and motion constraints for video anomaly detection.
A multi-scale network with adversarial training is proposed to generate more photo-realistic future frames in videos. A predictive neural network is designed ...
Dec 28, 2017 · This is the first work that leverages the difference between a predicted future frame and its ground truth to detect an abnormal event.
This repo is the official open-source of Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018 by Wen Liu, Weixin Luo, Dongze Lian and ...
Anomaly detection in videos refers to the identification of events that do not conform to expected behavior. However, almost all existing methods tackle the ...
This paper proposes a video anomaly detection algorithm based on the future frame prediction using Generative Adversarial Network (GAN) and attention mechanism.
Aug 15, 2023 · We introduce the task of future video prediction from a single frame, as a novel proxy-task for video anomaly detection.
Missing: Network | Show results with:Network
We model the future frame prediction as a two branch network to solve the inherent problem that RNN-based methods have when it comes to capturing short-term ...
This paper proposes to tackle the anomaly detection problem within a video prediction framework by introducing a motion (temporal) constraint in video ...
Our framework incorporates Convolutional Long Short-Term Memory (ConvLSTM), masked convolution, and attention mechanisms to enhance the detection accuracy.