Fine-Grained Action Detection
9 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Fine-Grained Action Detection
GTEA
MultiSports
Most implemented papers
Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection
knmac/LCDC_release
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ICCV 2019
Fine-grained action detection is an important task with numerous applications in robotics and human-computer interaction.
FineAction: A Fine-Grained Video Dataset for Temporal Action Localization
Temporal action localization (TAL) is an important and challenging problem in video understanding.
Few-Shot Temporal Action Localization with Query Adaptive Transformer
Further, a novel FS-TAL model is proposed which maximizes the knowledge transfer from training classes whilst enabling the model to be dynamically adapted to both the new class and each video of that class simultaneously.
Sports Video: Fine-Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2021
Sports video analysis is a prevalent research topic due to the variety of application areas, ranging from multimedia intelligent devices with user-tailored digests up to analysis of athletes' performance.
E^2TAD: An Energy-Efficient Tracking-based Action Detector
VITA-Group/21LPCV-UAV-Solution
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Video action detection (spatio-temporal action localization) is usually the starting point for human-centric intelligent analysis of videos nowadays.
Weakly-Supervised Temporal Action Detection for Fine-Grained Videos with Hierarchical Atomic Actions
lizhi1104/haan
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Action understanding has evolved into the era of fine granularity, as most human behaviors in real life have only minor differences.
Holistic Interaction Transformer Network for Action Detection
Actions are about how we interact with the environment, including other people, objects, and ourselves.
Sport Task: Fine Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2022
Since 2021, the task also provides a stroke detection challenge from unannotated, untrimmed videos.
Fine-Grained Action Detection with RGB and Pose Information using Two Stream Convolutional Networks
As participants of the MediaEval 2022 Sport Task, we propose a two-stream network approach for the classification and detection of table tennis strokes.
