SOTAVerified

Action Localization

Action Localization is finding the spatial and temporal co ordinates for an action in a video. An action localization model will identify which frame an action start and ends in video and return the x,y coordinates of an action. Further the co ordinates will change when the object performing action undergoes a displacement.

Papers

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Showing 176–200 of 369 papers

TitleStatusHype
DAP3D-Net: Where, What and How Actions Occur in Videos?—0
Cutup and Detect: Human Fall Detection on Cutup Untrimmed Videos Using a Large Foundational Video Understanding Model—0
Weakly-Supervised Action Localization and Action Recognition using Global-Local Attention of 3D CNN—0
Cross-Video Contextual Knowledge Exploration and Exploitation for Ambiguity Reduction in Weakly Supervised Temporal Action Localization—0
Learning to Refactor Action and Co-occurrence Features for Temporal Action Localization—0
Learning to track for spatio-temporal action localization—0
LLM-powered Query Expansion for Enhancing Boundary Prediction in Language-driven Action Localization—0
Localizing Actions from Video Labels and Pseudo-Annotations—0
Localizing Moments of Actions in Untrimmed Videos of Infants with Autism Spectrum Disorder—0
Cross-Attentional Audio-Visual Fusion for Weakly-Supervised Action Localization—0
Localizing Unseen Activities in Video via Image Query—0
LocATe: End-to-end Localization of Actions in 3D with Transformers—0
LoSA: Long-Short-range Adapter for Scaling End-to-End Temporal Action Localization—0
Low-Fidelity End-to-End Video Encoder Pre-training for Temporal Action Localization—0
Low-Fidelity Video Encoder Optimization for Temporal Action Localization—0
Low Pass Filter for Anti-aliasing in Temporal Action Localization—0
Towards Train-Test Consistency for Semi-supervised Temporal Action Localization—0
Marginalized Average Attentional Network for Weakly-Supervised Learning—0
Max-Margin Structured Output Regression for Spatio-Temporal Action Localization—0
Minimalistic Video Saliency Prediction via Efficient Decoder & Spatio Temporal Action Cues—0
Cricket stroke extraction: Towards creation of a large-scale cricket actions dataset—0
Modeling Spatio-Temporal Human Track Structure for Action Localization—0
Multi-Granularity Fusion Network for Proposal and Activity Localization: Submission to ActivityNet Challenge 2019 Task 1 and Task 2—0
A Better Baseline for AVA—0
Multi-modal Capsule Routing for Actor and Action Video Segmentation Conditioned on Natural Language Queries—0
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