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Online Action Detection

Online action detection is the task of predicting the action as soon as it happens in a streaming video without access to video frames in the future.

Papers

Showing 125 of 39 papers

TitleStatusHype
Colar: Effective and Efficient Online Action Detection by Consulting ExemplarsCode2
MiniROAD: Minimal RNN Framework for Online Action DetectionCode1
OadTR: Online Action Detection with TransformersCode1
Context-Enhanced Memory-Refined Transformer for Online Action DetectionCode1
Memory-and-Anticipation Transformer for Online Action UnderstandingCode1
Continual Transformers: Redundancy-Free Attention for Online InferenceCode1
Real-time Online Video Detection with Temporal Smoothing TransformersCode1
E2E-LOAD: End-to-End Long-form Online Action DetectionCode1
ActionSwitch: Class-agnostic Detection of Simultaneous Actions in Streaming VideosCode1
Long Short-Term Transformer for Online Action DetectionCode1
Rethinking Online Action Detection in Untrimmed Videos: A Novel Online Evaluation ProtocolCode0
Temporally smooth online action detection using cycle-consistent future anticipationCode0
Temporal Recurrent Networks for Online Action DetectionCode0
Text-driven Online Action DetectionCode0
The Instantaneous Accuracy: a Novel Metric for the Problem of Online Human Behaviour Recognition in Untrimmed VideosCode0
Two-Stream AMTnet for Action DetectionCode0
A Comprehensive Study on Temporal Modeling for Online Action DetectionCode0
Online Human Action Detection using Joint Classification-Regression Recurrent Neural NetworksCode0
Weakly Supervised Online Action Detection for Infant General MovementsCode0
Learning to Discriminate Information for Online Action DetectionCode0
Human Activity Recognition: A Spatio-temporal Image Encoding of 3D Skeleton Data for Online Action DetectionCode0
WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos0
A Novel Online Action Detection Framework from Untrimmed Video Streams0
Bridging the gap between Human Action Recognition and Online Action Detection0
Continual Low-Rank Scaled Dot-product Attention0
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