Generic Event Boundary Detection
10 papers with code • 2 benchmarks • 2 datasets
Kinetics
TAPOS
Most implemented papers
Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary Detection
mcg-nju/ddm
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CVPR 2022
Generic event boundary detection is an important yet challenging task in video understanding, which aims at detecting the moments where humans naturally perceive event boundaries.
Generic Event Boundary Detection: A Benchmark for Event Segmentation
This paper presents a novel task together with a new benchmark for detecting generic, taxonomy-free event boundaries that segment a whole video into chunks.
Winning the CVPR'2021 Kinetics-GEBD Challenge: Contrastive Learning Approach
hello-jinwoo/LOVEU-CVPR2021
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Generic Event Boundary Detection (GEBD) is a newly introduced task that aims to detect "general" event boundaries that correspond to natural human perception.
Generic Event Boundary Detection Challenge at CVPR 2021 Technical Report: Cascaded Temporal Attention Network (CASTANET)
In this work, we design a Cascaded Temporal Attention Network (CASTANET) for GEBD, which is formed by three parts, the backbone network, the temporal attention module, and the classification module.
Masked Autoencoders for Generic Event Boundary Detection CVPR'2022 Kinetics-GEBD Challenge
contentandmaterialportrait/mae-gebd
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In this paper, we apply Masked Autoencoders to improve algorithm performance on the GEBD tasks.
SC-Transformer++: Structured Context Transformer for Generic Event Boundary Detection
This report presents the algorithm used in the submission of Generic Event Boundary Detection (GEBD) Challenge at CVPR 2022.
Motion Aware Self-Supervision for Generic Event Boundary Detection
In this work, we address this issue by revisiting a simple and effective self-supervised method and augment it with a differentiable motion feature learning module to tackle the spatial and temporal diversities in the GEBD task.
Generic Event Boundary Detection in Video with Pyramid Features
th2l/GEBD-PyramidFeatureSimilarity
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In this study, we present an approach that considers the correlation between neighbor frames with pyramid feature maps in both spatial and temporal dimensions to construct a framework for localizing generic events in video.
MAE-GEBD:Winning the CVPR'2023 LOVEU-GEBD Challenge
contentandmaterialportrait/mae-gebd
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The Generic Event Boundary Detection (GEBD) task aims to build a model for segmenting videos into segments by detecting general event boundaries applicable to various classes.
Local Compressed Video Stream Learning for Generic Event Boundary Detection
gx77/lcvsl
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Specifically, we use lightweight ConvNets to extract features of the P-frames in the GOPs and spatial-channel attention module (SCAM) is designed to refine the feature representations of the P-frames based on the compressed information with bidirectional information flow.
