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Summary: Computer vision has emerged as a key technology for applications like traffic surveillance, particularly in detecting anomalies in public places. However, there is a lack of systematic survey on vision-guided anomaly detection techniques. This study aims to address the gap by analyzing various methods and providing future directions for research in this area.
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Article
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Gorkem Algan et al.
Summary: Deep neural networks have made significant progress in image classification systems, but the excessive labeled data required for adequate training poses challenges due to label noise. This paper categorizes methodologies into noise model based and noise model free methods, with the former aiming to estimate noise structure and avoid adverse effects, and the latter focusing on inherently noise robust algorithms using approaches like robust losses.
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Ajeet Ram Pathak et al.
Summary: This paper proposes a deep learning based topic-level sentiment analysis model that utilizes online latent semantic indexing and topic-level attention mechanism to detect and analyze user sentiments towards discussed topics on social media platforms in real-time.
APPLIED SOFT COMPUTING
(2021)
Proceedings Paper
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Jie Wu et al.
Summary: In this paper, a box-level tracking and refinement algorithm for traffic anomaly detection is proposed, which utilizes auxiliary detection cues to promote abnormal predictions. The approach achieved second place in the NVIDIA AI CITY 2021 CHALLENGE, showing superior performance.
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(2021)
Proceedings Paper
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Armstrong Aboah et al.
Summary: An intelligent traffic monitoring system must detect anomalies such as traffic accidents in real time. This paper introduces a Decision-Tree enabled approach powered by deep learning for extracting anomalies from traffic cameras while accurately estimating the start and end times of the anomalous event, with promising experimental validation results.
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Jingyuan Chen et al.
Summary: The paper proposes a dual-modality modularized methodology for detecting abnormal vehicles, which integrates background modeling, vehicle tracking, mask construction, ROI backtracking, and dual-modality tracing modules. Experimental results on the Track 4 testset of the NVIDIA 2021 AI City Challenge demonstrate the effectiveness of the framework with an F1-Score of 0.9302 and a root mean square error (RMSE) of 3.4039.
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Proceedings Paper
Computer Science, Artificial Intelligence
Keval Doshi et al.
Summary: An efficient approach for video anomaly detection in traffic videos is proposed, which is capable of running at edge devices and consists of several modules for scene processing and analysis. Experimental results show promising performance of the proposed framework in the 2021 AI City Challenge competition.
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Yuxiang Zhao et al.
Summary: Detecting traffic anomalies is crucial for intelligent city transportation management systems. This paper proposes a framework that includes preprocessing, a dynamic tracking module, and post-processing, which effectively detects anomalies in the traffic scene. The framework achieved 1st place in the NVIDIA AI CITY 2021 leaderboard, showcasing its effectiveness in traffic anomaly detection.
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(2020)
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(2019)
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(2019)
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(2006)
