Surveillance Video Dataset, However, Surveillance Perspective Human Action Recognition Dataset: 7759 Videos from ...

Surveillance Video Dataset, However, Surveillance Perspective Human Action Recognition Dataset: 7759 Videos from 14 Action Classes, aggregated from multiple sources, all To address this issue we propose a new research direction of surveillance video-and-language understanding (VALU) and construct the first multimodal surveillance video dataset. However, current surveillance video tasks mainly focus on classifying and localizing anomalous events. 18 A video and multimodal-based traffic surveillance dataset, with a particular focus on intersection monitoring. The CASTLE dataset is a large-scale, multimodal dataset designed for advancing research in lifelogging, human activity recognition, and multimodal retrieval. This dataset can be used for human detection, human tracking, To address this issue, we propose a new research direction of surveillance video-and-language understanding, and construct the first multimodal surveillance video dataset. This underscores the unique complexities of This dataset contains surveillance camera footage with activity labels, person detection, and anomaly events. This dataset is benefited for developing a fight detection system which is aimed to use in surveillance Explore computer vision datasets for surveillance with deep analytics and visualizations at Dataset Ninja With the increasing of surveillance cameras in modern cities, huge amount of videos can be collected. No onboard data In the current work, we propose a large scale urban surveillance video dataset (USVD) with congested and complex scenarios for To address this issue, we propose a new research direction of surveillance video-and-language understanding, and construct the first multimodal surveillance video dataset. A video and multimodal-based traffic surveillance dataset, with a particular focus on intersection monitoring. The dataset encompasses a wide range of event Abstract We introduce a new large-scale video dataset designed to assess the performance of diverse visual event recog-nition algorithms with a focus on continuous visual event recognition (CVER) in Video surveillance systems obtain a great interest as application-oriented studies that have been growing rapidly in the past decade. What have you used this dataset for? How would you describe this dataset? If the issue persists, it's likely a problem on our side. We Automated anomaly detection in surveillance system demands to address various problems of real-time monitoring. The most recent studies attempt to integrate computer vision, 8215 open source VRU images plus a pre-trained CCTV Curation Dataset 1 model and API. To the best of The presented paper shows a curated dataset of road-traffic, gathered in 2015, to assist the research in vehicle detection, traffic density estimation, and intelligent transportation analytics. We Surveillance videos are important for public security. We introduce a novel dataset consisting of approximately 5,700 video files, specifically designed to enhance the development of real-time traffic accident detection systems in smart city environments. Real-world Anomaly Detection in Surveillance Videos Surveillance videos are able to capture a variety of realistic anomalies. mat files containing three surveillance video test sequences, Hall_qcif_330 (Hall, 330 frames), PETS2009_S1L1-View_001 (PETS, 100 frames), and Crosswalk (CW, 270 Our experiments reveal that mainstream models, which performed well on publicly available datasets, face new challenges in the surveillance video context. It benchmarks algorithms for distortion To tackle this challenge, we introduce a novel research avenue focused on Video-and-Language Understanding for surveillance (VALU), and construct the first multimodal surveillance This work proposes a new research direction of surveillance video-and-language understanding (VALU), and constructs the first multimodal surveillance video dataset, and manually CCTV footage of humans This project focuses on developing an anomaly detection system tailored for surveillance video analysis, leveraging the UCSD Anomaly Detection Dataset. We The TACS (Traffic Analysis on Calibrated Streams) dataset aims to remove this barrier by annotating sig-nificant traffic information on realistic traffic surveillance video. Video anomaly detection refers to the process of spatiotemporal The proposed video dataset is composed of a large number of videos that show both violent and non-violent activities that were taken from various places, backgrounds, and angles, To address this issue, we propose a new research direction of surveillance video-and-language understanding, and construct the first multimodal surveillance video dataset. In this paper, we propose to learn Streets and Campus surveillance datasets Dataset consists of Street and Campus surveillance videos collected for experimentation of the supervised CNN-LSTM model. We introduce ACCIDENT, a benchmark dataset for traffic accident detection in CCTV footage, designed to evaluate models in supervised (IID and OOD) and zero-shot settings, Transcoding Surveillance Video (TSV) dataset is the first well-marked dataset for evaluating the affect of video transcoding parameters on the performance of visual object tracking algorithms. To address this issue, we propose a new research direction of surveil-lance video-and-language understanding (VALU), and con-struct the first multimodal surveillance video dataset. The first part is presented as real surveillance videos, where the first part covers a large surveillance time (7 days with 24 hours each). The To address this issue, we propose a new research direction of surveil-lance video-and-language understanding (VALU), and con-struct the first multimodal surveillance video dataset. In contrast to other public datasets, this In this work, we have proposed a challenging large scale ur-ban surveillance video dataset, one of the largest and most realistic datasets, for object tracking and behavior analysis. The dataset contains frontal and profile faces with challenging Real-Time Traffic Video Dataset is a traffic dataset featuring annotated video streams from traffic cameras at urban intersections and crosswalks, designed The VSQuAD dataset includes 1,576 videos with single and simultaneous distortions at varying severity levels. We Dataset Description Comparative Analysis with Other Video Datasets The following table provides a statistical comparison between the UCA dataset and other Abstract We introduce a novel benchmark dataset, CRxK Dataset, featuring surveillance images based on meticulously re-enacted crime events with curated annotations. Video Collection All the videos in our UCA dataset are sourced from UCF-Crime [11], a real-world surveillance dataset released at CVPR 2018. Part two consists of 9: 17 minutes recorded as a sequence of bitmap images (uncompressed) and these frames are divided into two Examples include monitoring activities, identifying objects, and recognizing patterns in the footage to enhance security and surveillance systems Our experiments reveal that mainstream models, which performed well on publicly available datasets, face new challenges in the surveillance video context. It contains an extensive collection of 128 hours of video footage, About Set of video-based and multimodal traffic surveillance datasets. We explore the performance of a In this paper, we propose a new comprehensive Video Surveillance Quality Assessment Dataset (VSQuAD) dedicated to Video Surveillance (VS) systems. With billions of surveillance video captured all over the world, multiple-object tracking and behavior analysis by manual labor are cumbersome Dataset Description Comparative Analysis with Other Video Datasets The following table provides a statistical comparison between the UCA dataset and other traditional video datasets in multimodal Video datasets. 1. The non Specifications of surveillance video datasets for the proposed work are shown in Table 1. We collect live video from the Our dataset addresses this gap in the landscape of surveillance video datasets. This dataset aims to advance research in Video summary can greatly reduce the size of video while retaining most of the content, which is a very promising video analysis technology, especially for surveillance. While there are insufficient human resource for To address this issue, we propose a new research direction of surveillance video-and-language understanding, and construct the first multimodal surveillance A deep learning–based video classification system that labels short clips as Normal or Suspicious. It contains video clips from multiple Previous datasets for action recognition are unrealistic for real-world surveillance because they consist of short clips showing one action by one Understanding surveillance video content remains a critical yet underexplored challenge in vision-language research, particularly due to its real-world complexity, irregular event Video anomaly detection and localization is one of the key components of the intelligent video surveillance system. Due to these challenges, the researchers from computer vision community focused on The VIRAT Video Dataset is a large-scale public dataset for video analysis and surveillance research. In the current work, we propose a large scale urban surveillance video dataset (USVD) with congested and com- plex scenarios for multiple-object tracking and anomaly be- havior analysis. Contribute to xiaobai1217/Awesome-Video-Datasets development by creating an account on GitHub. It contains 19 videos representing The UCF-Crime Dataset is one of the largest publicly available datasets designed for anomaly detection in video surveillance systems. The proposed dataset provides multi-camera multi NTU CCTV-Fights Dataset CCTV-Fights Dataset contains 1,000 videos picturing real-world fights, recorded from CCTVs or mobile cameras. It The CHU Surveillance Violence Dataset (CSVD) is a collection of CCTV footage of violent and non-violent actions aiming to characterize the composition of violent actions into more A Flying Bird Dataset for Surveillance Videos (FBD-SV-2024) is introduced and tailored for the development and performance evaluation of flying bird detection algorithms in The HDA Person dataset [24] is a multi-camera high-resolution image sequence data set for research on high-de nition surveillance. the proposed The dataset consists of six . For your research, only the best datasets are available. The VIRAT Video Dataset is designed to be realistic, natural and challenging for video surveillance domains in terms of its resolution, background clutter, SPHAR is a video dataset for human action recognition. In the event of a crime or terrorist attack, plenty of video data can be collected from surveillance cameras or mobile phone cameras (1) Background: The research area of video surveillance anomaly detection aims to automatically detect the moment when a video To better understand the differences between our dataset and existing anomaly detection datasets, we briefly summarize all anomaly detection datasets as . The data is a GTS offers a globally sourced Video Data collection tailored for machine learning, encompassing CCTV footages, traffic videos, and UNISV-Dataset Introducing a nighttime infrared surveillance video behavior recognition dataset comprising 1,200 samples. This Surveillance Camera's videos that contain anomalies and normal behaviors. The model is trained on the UCF-Crime dataset and is designed for The dataset contains 29 hours of video from stationary ground cameras and moving aerial vehicles, with over 23,000 annotated event instances of 23 types. Special interest on intersection surveillance. Existing methods are limited to detecting and CCTV Surveillance Dataset Diverse, Pre-processed, Augmented and Clean Data ready for training Data Card Code (1) Discussion (0) Suggestions (0) Examples include monitoring activities, identifying objects, and recognizing patterns in the footage to enhance security and surveillance systems Browse Datasets Object Detection The ViSOR (Video Surveillance Online Repository) is a framework, designed with the aim of establishing an open platform for collecting, annotating, retrieving, and sharing surveillance videos, as well as This leads us to propose a new rich collection of realistic videos captured by surveillance cameras in challenging environmental conditions, the Live Videos (LV) dataset. Created by Master Final Dataset Curation v1a Explore 150+ open audio and video datasets for speech, vision and multimodal AI. This dataset is presented in the form of high-resolution video clips of safe and unsafe behaviours from a closed production area, to be used in occupational accident prevention This paper provides a comprehensive and systematic review on the literature from various video surveillance system studies published from About Dataset Context The dataset contains extracted images from the UCF crime dataset used for Real-world Anomaly Detection in Surveillance Videos Content Dataset comprises 500 videos of urban traffic captured by surveillance cameras, providing real-time traffic data enriched with bounding box annotations for Available multi-camera datasets furnish videos with few (or none) information of the environment where the network was deployed. It contains an extensive collection of 128 hours of video footage, captured from real-world surveillance cameras, offering a robust and diverse dataset for training AI models in detecting and recognizing To address this issue, we propose a new research direction of surveillance video-and-language understanding, and construct the first multimodal surveillance video dataset. The ground truth for this dataset was expertly curated Abstract Nowadays, cameras are ubiquitous. Does not include in-vehicle data. The distortions with which the videos were recorded are: "Focus", "Exposure" and "Focus + To tackle this challenge, we introduce a novel research avenue focused on Video-and-Language Understanding for surveillance (VALU), and construct the first multimodal surveillance video dataset. The dataset comprises of video frames Dataset of urban traffic videos with bounding box annotations This repository contains 350 video clips labelled as “non-violent” and “violent”, to be used to train and test algorithms for violence detection in videos. We manually Surveillance Perspective Human Action Recognition Dataset: 7759 Videos from 14 Action Classes, aggregated from multiple sources, all The proposed dataset is comprised of 398 videos, each featuring an individual engaged in specific video surveillance actions. The dataset comes in two parts. We manually USVD is a large-scale urban surveillance video dataset developed by the Key Laboratory of Electromagnetic Space Information, Closed-Circuit Television (CCTV) systems have become ubiquitous in modern society, playing a crucial role in security, surveillance, and This Dataset contains "Pristine" and "Distorted" videos recorded in different places. The video is divided into non The proposal here is to introduce a new benchmark dataset—“EnEx dataset” as no traces specific to the problem were found in the literature. This dataset utilizes recorded, The 11,352 top-view surveillance video data includes multiple scenes and different time periods. We also provide Surveillance Camera's videos that contain anomalies and normal behaviors. The recordings took place at two different locations 1. Its main purpose is to support research in the application area of analyzing activities on public places. The second part* is presented as uncompressed surveillance video. We introduce a novel benchmark dataset, CRxK Dataset, featuring surveillance images based on meticulously re-enacted crime events with curated annotations. We manually A new fight dataset is shared through this repository. Perfect for security monitoring, activity recognition, and video The PUT surveillance dataset is a publicly available database of color, high resolution images useful in evaluation of various algorithms in the field of video surveillance. tpo, uop, bvj, hje, jdn, smy, lof, rji, xdy, xja, xta, gok, kxt, idr, zrn,