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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

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Showing 1–25 of 39 papers

TitleStatusHype
Colar: Effective and Efficient Online Action Detection by Consulting ExemplarsCode2
Context-Enhanced Memory-Refined Transformer for Online Action DetectionCode1
Real-time Online Video Detection with Temporal Smoothing TransformersCode1
Continual Transformers: Redundancy-Free Attention for Online InferenceCode1
MiniROAD: Minimal RNN Framework for Online Action DetectionCode1
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
OadTR: Online Action Detection with TransformersCode1
Memory-and-Anticipation Transformer for Online Action UnderstandingCode1
Linear-time Online Action Detection From 3D Skeletal Data Using Bags of Gesturelets—0
MALT: Multi-scale Action Learning Transformer for Online Action Detection—0
WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos—0
A Novel Online Action Detection Framework from Untrimmed Video Streams—0
Bridging the gap between Human Action Recognition and Online Action Detection—0
Continual Low-Rank Scaled Dot-product Attention—0
Exploring Temporal Context and Human Movement Dynamics for Online Action Detection in Videos—0
GateHUB: Gated History Unit with Background Suppression for Online Action Detection—0
Information Elevation Network for Fast Online Action Detection—0
JOADAA: joint online action detection and action anticipation—0
LAP-Net: Adaptive Features Sampling via Learning Action Progression for Online Action Detection—0
Learning to Discriminate Information for Online Action Detection: Analysis and Application—0
Object Aware Egocentric Online Action Detection—0
Online Action Detection—0
Online Action Detection in Streaming Videos with Time Buffers—0
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