Action Detection
233 papers with code • 11 benchmarks • 33 datasets
Action Detection aims to find both where and when an action occurs within a video clip and classify what the action is taking place. Typically results are given in the form of action tublets, which are action bounding boxes linked across time in the video. This is related to temporal localization, which seeks to identify the start and end frame of an action, and action recognition, which seeks only to classify which action is taking place and typically assumes a trimmed video.
Benchmarks
These leaderboards are used to track progress in Action Detection
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Libraries
Use these libraries to find Action Detection models and implementationsDatasets
ActivityNet
Charades
THUMOS14
JHMDB
AVA
MultiTHUMOS
TVSeries
Toyota Smarthome Dataset
Subtasks
Latest papers with no code
High-speed Low-consumption sEMG-based Transient-state micro-Gesture Recognition
The accuracy of the proposed SNN is 83. 85% and 93. 52% on the two datasets respectively.
Fast Low-parameter Video Activity Localization in Collaborative Learning Environments
Research on video activity detection has primarily focused on identifying well-defined human activities in short video segments.
Joint Activity-Delay Detection and Channel Estimation for Asynchronous Massive Random Access: A Free Probability Theory Approach
Grant-free random access (RA) has been recognized as a promising solution to support massive connectivity due to the removal of the uplink grant request procedures.
Channel-Combination Algorithms for Robust Distant Voice Activity and Overlapped Speech Detection
A channel-number invariant loss is proposed to learn a unique feature representation regardless of the number of available microphones.
Device Activity Detection and Channel Estimation for Millimeter-Wave Massive MIMO
Different from traditional compressed sensing (CS) methods that only use the sparsity of user activities, we develop several Approximate Message Passing (AMP) based CS algorithms by exploiting the sparsity of user activities and mmWave channels.
A Computer Vision Based Approach for Stalking Detection Using a CNN-LSTM-MLP Hybrid Fusion Model
Criminal and suspicious activity detection has become a popular research topic in recent years.
Joint User Detection and Localization in Near-Field Using Reconfigurable Intelligent Surfaces
This letter studies the problem of jointly detecting active user equipments (UEs) and estimating their location in the near field, wherein the base station (BS) is unaware of the number of active (or inactive) UEs and their positions.
Activity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian Approach
This problem is even more severe in cell-free networks as there are many of these parameters to be acquired.
Cutup and Detect: Human Fall Detection on Cutup Untrimmed Videos Using a Large Foundational Video Understanding Model
The results are promising for real-time application, and the falls are detected on video level with a state-of-the-art 0. 96 F1 score on the HQFSD dataset under the given experimental settings.
Multi-Input Multi-Output Target-Speaker Voice Activity Detection For Unified, Flexible, and Robust Audio-Visual Speaker Diarization
The proposed method can take audio-visual input and leverage the speaker's acoustic footprint or lip track to flexibly conduct audio-based, video-based, and audio-visual speaker diarization in a unified sequence-to-sequence framework.
