Event Detection

190 papers with code • 2 benchmarks • 7 datasets

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Most implemented papers

CNN Architectures for Large-Scale Audio Classification

towhee-io/towhee 29 Sep 2016

Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio.

Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks

UKPLab/emnlp2017-bilstm-cnn-crf 21 Jul 2017

Selecting optimal parameters for a neural network architecture can often make the difference between mediocre and state-of-the-art performance.

What Makes Training Multi-Modal Classification Networks Hard?

facebookresearch/R2Plus1D CVPR 2020

Consider end-to-end training of a multi-modal vs. a single-modal network on a task with multiple input modalities: the multi-modal network receives more information, so it should match or outperform its single-modal counterpart.

Recurrent Neural Networks for Polyphonic Sound Event Detection in Real Life Recordings

yardencsGitHub/tf_syllable_segmentation_annotation 4 Apr 2016

In this paper we present an approach to polyphonic sound event detection in real life recordings based on bi-directional long short term memory (BLSTM) recurrent neural networks (RNNs).

Adaptive pooling operators for weakly labeled sound event detection

marl/autopool 26 Apr 2018

In this work, we treat SED as a multiple instance learning (MIL) problem, where training labels are static over a short excerpt, indicating the presence or absence of sound sources but not their temporal locality.

Literary Event Detection

dbamman/litbank ACL 2019

In this work we present a new dataset of literary events{---}events that are depicted as taking place within the imagined space of a novel.

Embed2Detect: Temporally Clustered Embedded Words for Event Detection in Social Media

HHansi/Embed2Detect 10 Jun 2020

Social media is becoming a primary medium to discuss what is happening around the world.

A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video

lilygeorgescu/AED 27 Aug 2020

Following the standard formulation of abnormal event detection as outlier detection, we propose a background-agnostic framework that learns from training videos containing only normal events.

ACCDOA: Activity-Coupled Cartesian Direction of Arrival Representation for Sound Event Localization and Detection

sharathadavanne/seld-dcase2021 29 Oct 2020

Conventional NN-based methods use two branches for a sound event detection (SED) target and a direction-of-arrival (DOA) target.