Event Detection
221 papers with code • 2 benchmarks • 7 datasets
Benchmarks
These leaderboards are used to track progress in Event Detection
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Libraries
Use these libraries to find Event Detection models and implementations
ROAD
MAVEN-ERE
OpenTTGames
Brazilian Protest
MUSIED
Most implemented papers
ACCDOA: Activity-Coupled Cartesian Direction of Arrival Representation for Sound Event Localization and Detection
Conventional NN-based methods use two branches for a sound event detection (SED) target and a direction-of-arrival (DOA) target.
Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs
The complexity and streaming nature of social messages make it appealing to address social event detection in an incremental learning setting, where acquiring, preserving, and extending knowledge are major concerns.
ROAD: The ROad event Awareness Dataset for Autonomous Driving
We also report the performance on the ROAD tasks of Slowfast and YOLOv5 detectors, as well as that of the winners of the ICCV2021 ROAD challenge, which highlight the challenges faced by situation awareness in autonomous driving.
Couple Learning for semi-supervised sound event detection
The recently proposed Mean Teacher method, which exploits large-scale unlabeled data in a self-ensembling manner, has achieved state-of-the-art results in several semi-supervised learning benchmarks.
RCT: Random Consistency Training for Semi-supervised Sound Event Detection
Audio-WestlakeU/RCT-Random-Consistency-Training
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Sound event detection (SED), as a core module of acoustic environmental analysis, suffers from the problem of data deficiency.
Self-supervised Audio Teacher-Student Transformer for Both Clip-level and Frame-level Tasks
In order to tackle both clip-level and frame-level tasks, this paper proposes Audio Teacher-Student Transformer (ATST), with a clip-level version (named ATST-Clip) and a frame-level version (named ATST-Frame), responsible for learning clip-level and frame-level representations, respectively.
Performance and energy balance: a comprehensive study of state-of-the-art sound event detection systems
In recent years, deep learning systems have shown a concerning trend toward increased complexity and higher energy consumption.
A Comprehensive Python Library for Deep Learning-Based Event Detection in Multivariate Time Series Data and Information Retrieval in NLP
In this paper, we present a new deep learning supervised method for detecting events in multivariate time series data.
EigenEvent: An Algorithm for Event Detection from Complex Data Streams in Syndromic Surveillance
Experimental results on hundred sets of benchmark data reveals that EigenEvent presents a better overall performance comparing state-of-the-art, in particular in terms of the false alarm rate.
