Video Anomaly Detection

Benchmarks archive 2025-07-28

15 leaderboard tables shown for this task, 14 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 15 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

17 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 111 papers with code (262 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Adversarially Learned One-Class Classifier for Novelty Detection
  25 Feb 2018 5 repositories listed
  Our architecture is composed of two deep networks, each of which trained by competing with each other while collaborating to understand the underlying concept in the target class, and then classify the testing samples.
• An Attribute-based Method for Video Anomaly Detection
  1 Dec 2022 4 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  Video anomaly detection (VAD) identifies suspicious events in videos, which is critical for crime prevention and homeland security.
• Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning
  25 Jan 2021 3 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)
  To address this issue, we introduce a novel and theoretically sound method, named Robust Temporal Feature Magnitude learning (RTFM), which trains a feature magnitude learning function to effectively recognise the…
• When, Where, and What? A New Dataset for Anomaly Detection in Driving Videos
  6 Apr 2020 3 repositories listed
  A new spatial-temporal area under curve (STAUC) evaluation metric is proposed and used with DoTA.
• Quo Vadis, Anomaly Detection? LLMs and VLMs in the Spotlight
  24 Dec 2024 2 repositories listed
  Video anomaly detection (VAD) has witnessed significant advancements through the integration of large language models (LLMs) and vision-language models (VLMs), addressing critical challenges such as interpretability,…
• Weakly-Supervised Video Anomaly Detection with Snippet Anomalous Attention
  28 Sep 2023 2 repositories listed
  Our approach takes into account snippet-level encoded features without the supervision of pseudo labels.
• CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly Detection
  9 Dec 2022 2 repositories listed
  Video anomaly detection (VAD) -- commonly formulated as a multiple-instance learning problem in a weakly-supervised manner due to its labor-intensive nature -- is a challenging problem in video surveillance where the…
• Unsupervised Traffic Accident Detection in First-Person Videos
  2 Mar 2019 2 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  Recognizing abnormal events such as traffic violations and accidents in natural driving scenes is essential for successful autonomous driving and advanced driver assistance systems.
• Learning Temporal Regularity in Video Sequences
  15 Apr 2016 2 repositories listed
  Perceiving meaningful activities in a long video sequence is a challenging problem due to ambiguous definition of 'meaningfulness' as well as clutters in the scene.
• Sequential keypoint density estimator: an overlooked baseline of skeleton-based video anomaly detection
  23 Jun 2025 1 repository listed
  In practice, our anomaly score is a weighted sum of per-keypoint log-conditionals, where the weights account for the confidence of the underlying keypoint detector.
• SmartHome-Bench: A Comprehensive Benchmark for Video Anomaly Detection in Smart Homes Using Multi-Modal Large Language Models
  15 Jun 2025 1 repository listed
  To bridge this gap, we introduce SmartHome-Bench, the first comprehensive benchmark specially designed for evaluating VAD in smart home scenarios, focusing on the capabilities of multi-modal large language models…
• Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive Mapping
  13 Jun 2025 1 repository listed
  Federated weakly supervised video anomaly detection represents a significant advancement in privacy-preserving collaborative learning, enabling distributed clients to train anomaly detectors using only video-level…
• Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation
  13 Jun 2025 1 repository listed Syntology ran 8 of 10 samples · 2 unverified · 10 pointer-only (licence)
  Self-supervised learning (SSL) has achieved major advances in natural images and video understanding, but challenges remain in domains like echocardiography (heart ultrasound) due to subtle anatomical structures,…
• Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought
  26 May 2025 1 repository listed
  In this paper, we propose a new task named Video Anomaly Reasoning (VAR), which aims to enable deep analysis and understanding of anomalies in the video by requiring MLLMs to think explicitly before answering.
• Uncertainty-Weighted Image-Event Multimodal Fusion for Video Anomaly Detection
  5 May 2025 1 repository listed
  Most existing video anomaly detectors rely solely on RGB frames, which lack the temporal resolution needed to capture abrupt or transient motion cues, key indicators of anomalous events.
• ProDisc-VAD: An Efficient System for Weakly-Supervised Anomaly Detection in Video Surveillance Applications
  4 May 2025 1 repository listed
  Weakly-supervised video anomaly detection (WS-VAD) using Multiple Instance Learning (MIL) suffers from label ambiguity, hindering discriminative feature learning.
• VADMamba: Exploring State Space Models for Fast Video Anomaly Detection
  27 Mar 2025 1 repository listed
  Video anomaly detection (VAD) methods are mostly CNN-based or Transformer-based, achieving impressive results, but the focus on detection accuracy often comes at the expense of inference speed.
• UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networks
  17 Mar 2025 1 repository listed
  This work explores the potential application of dynamic information from event data in video anomaly detection.
• Video Anomaly Detection with Structured Keywords
  7 Mar 2025 1 repository listed
  We present a novel, lightweight pipeline for anomaly classification using keyword weights.
• AnyAnomaly: Zero-Shot Customizable Video Anomaly Detection with LVLM
  6 Mar 2025 1 repository listed
  To address these challenges, this study proposes customizable video anomaly detection (C-VAD) technique and the AnyAnomaly model.
• HSTforU: anomaly detection in aerial and ground-based videos with hierarchical spatio-temporal transformer for U-net
  3 Jan 2025 1 repository listed
  Anomaly detection is to identify abnormal events against normal ones within surveillance videos mainly collected in ground-based settings.
• Dual Conditioned Motion Diffusion for Pose-Based Video Anomaly Detection
  23 Dec 2024 1 repository listed
  We address pose-based video anomaly detection and introduce a novel framework called Dual Conditioned Motion Diffusion (DCMD), which enjoys the advantages of both approaches.
• Video Anomaly Detection with Motion and Appearance Guided Patch Diffusion Model
  12 Dec 2024 1 repository listed
  To address this, we introduce innovative motion and appearance conditions that are seamlessly integrated into our patch diffusion model.
• Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly Detection
  4 Dec 2024 1 repository listed
  By guiding the diffusion model with observed high-frequency information, we prioritize the reconstruction of low-frequency components, enabling more accurate and robust anomaly detection.
• Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy vs. Performance
  24 Oct 2024 1 repository listed
  We evaluated the approaches on publicly available privacy and VAD data sets to examine the strengths and weaknesses of the different anonymization techniques and highlight the promising efficacy of our approach.
• MTFL: Multi-Timescale Feature Learning for Weakly-Supervised Anomaly Detection in Surveillance Videos
  8 Oct 2024 1 repository listed
  Detection of anomaly events is relevant for public safety and requires a combination of fine-grained motion information and contextual events at variable time-scales.
• VideoPatchCore: An Effective Method to Memorize Normality for Video Anomaly Detection
  24 Sep 2024 1 repository listed
  Inspired by PatchCore, our approach introduces a structure that prioritizes memory optimization and configures three types of memory tailored to the characteristics of video data.
• PoseWatch: A Transformer-based Architecture for Human-centric Video Anomaly Detection Using Spatio-temporal Pose Tokenization
  27 Aug 2024 1 repository listed
  Video Anomaly Detection (VAD) presents a significant challenge in computer vision, particularly due to the unpredictable and infrequent nature of anomalous events, coupled with the diverse and dynamic environments in…
• PHEVA: A Privacy-preserving Human-centric Video Anomaly Detection Dataset
  26 Aug 2024 1 repository listed
  This study benchmarks state-of-the-art methods on PHEVA using a comprehensive set of metrics, including the 10% Error Rate (10ER), a metric used for anomaly detection for the first time providing insights relevant to…
• What Matters in Autonomous Driving Anomaly Detection: A Weakly Supervised Horizon
  10 Aug 2024 1 repository listed
  While recent developments in weakly-supervised VAD methods have shown remarkable progress in detecting critical real-world anomalies in static camera scenario, the development and validation of such methods are yet to…

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.