Action Quality Assessment
22 papers with code • 6 benchmarks • 7 datasets
Assessing/analyzing/quantifying how well an action was performed.
Benchmarks
These leaderboards are used to track progress in Action Quality Assessment
Latest papers
LOGO: A Long-Form Video Dataset for Group Action Quality Assessment
Action quality assessment (AQA) has become an emerging topic since it can be extensively applied in numerous scenarios.
Multimodal Action Quality Assessment
To leverage multimodal information for AQA, i. e., RGB, optical flow and audio information, we propose a Progressive Adaptive Multimodal Fusion Network (PAMFN) that separately models modality-specific information and mixed-modality information.
Multi-Stage Contrastive Regression for Action Quality Assessment
In recent years, there has been growing interest in the video-based action quality assessment (AQA).
QAFE-Net: Quality Assessment of Facial Expressions with Landmark Heatmaps
Beyond FER, pain estimation methods assess levels of intensity in pain expressions, however assessing the quality of all facial expressions is of critical value in health-related applications.
PECoP: Parameter Efficient Continual Pretraining for Action Quality Assessment
The limited availability of labelled data in Action Quality Assessment (AQA), has forced previous works to fine-tune their models pretrained on large-scale domain-general datasets.
Fine-grained Action Analysis: A Multi-modality and Multi-task Dataset of Figure Skating
MMFS, which possesses action recognition and action quality assessment, captures RGB, skeleton, and is collected the score of actions from 11671 clips with 256 categories including spatial and temporal labels.
MMASD: A Multimodal Dataset for Autism Intervention Analysis
This work presents a novel privacy-preserving open-source dataset, MMASD as a MultiModal ASD benchmark dataset, collected from play therapy interventions of children with Autism.
Action Quality Assessment with Temporal Parsing Transformer
Action Quality Assessment(AQA) is important for action understanding and resolving the task poses unique challenges due to subtle visual differences.
FineDiving: A Fine-grained Dataset for Procedure-aware Action Quality Assessment
Most existing action quality assessment methods rely on the deep features of an entire video to predict the score, which is less reliable due to the non-transparent inference process and poor interpretability.
Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment
To that end, we propose to learn exercise-oriented image and video representations from unlabeled samples such that a small dataset annotated by experts suffices for supervised error detection.