Fine-grained Action Recognition

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

18 shown of 18 papers with code (38 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment
  8 Apr 2019 5 repositories listed
  Can performance on the task of action quality assessment (AQA) be improved by exploiting a description of the action and its quality?
• Unsupervised Feature Learning of Human Actions as Trajectories in Pose Embedding Manifold
  6 Dec 2018 3 repositories listed
  In this work we propose a novel temporal pose-sequence modeling framework, which can embed the dynamics of 3D human-skeleton joints to a continuous latent space in an efficient manner.
• Revealing Single Frame Bias for Video-and-Language Learning
  7 Jun 2022 2 repositories listed Syntology ran 4 of 12 samples · 8 unverified
  Training an effective video-and-language model intuitively requires multiple frames as model inputs.
• ConvGRU in Fine-grained Pitching Action Recognition for Action Outcome Prediction
  18 Aug 2020 2 repositories listed
  Considering that the different outcomes are closely connected to the subtle differences in actions, fine-grained action recognition is a practical method for action outcome prediction.
• HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN
  10 Dec 2019 2 repositories listed
  The hallucination task is treated as an auxiliary task, which can be used with any other action related task in a multitask learning setting.
• SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization
  2 Jan 2025 1 repository listed
  Experiments show that SeFAR achieves state-of-the-art performance on two FAR datasets, FineGym and FineDiving, across various data scopes.
• Pre-training for Action Recognition with Automatically Generated Fractal Datasets
  26 Nov 2024 1 repository listed
  We extend this trend to the video domain applying it to the task of action recognition.
• Enhancing Action Recognition by Leveraging the Hierarchical Structure of Actions and Textual Context
  28 Oct 2024 1 repository listed
  In this study, we present a novel approach to improve action recognition by exploiting the hierarchical organization of actions and by incorporating contextualized textual information, including location and prior…
• Understanding Long Videos with Multimodal Language Models
  25 Mar 2024 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 1 pointer-only (licence)
  Our resulting Multimodal Video Understanding (MVU) framework demonstrates state-of-the-art performance across multiple video understanding benchmarks.
• Fine-grained Action Analysis: A Multi-modality and Multi-task Dataset of Figure Skating
  6 Jul 2023 1 repository listed
  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.
• Real-time Action Recognition for Fine-Grained Actions and The Hand Wash Dataset
  13 Oct 2022 1 repository listed
  In this paper we present a three-stream algorithm for real-time action recognition and a new dataset of handwash videos, with the intent of aligning action recognition with real-world constraints to yield effective…
• Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition
  3 Sep 2021 1 repository listed
  This leads to poor accuracy when downstream tasks, such as action recognition, depend on pose.
• Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-Learning
  15 Aug 2021 1 repository listed
  Fine-grained action recognition is attracting increasing attention due to the emerging demand of specific action understanding in real-world applications, whereas the data of rare fine-grained categories is very limited.
• Sharing Pain: Using Pain Domain Transfer for Video Recognition of Low Grade Orthopedic Pain in Horses
  21 May 2021 1 repository listed
  Moreover, we present a human expert baseline for the problem, as well as an extensive empirical study of various domain transfer methods and of what is detected by the pain recognition method trained on clean…
• Few-shot Action Recognition with Prototype-centered Attentive Learning
  20 Jan 2021 1 repository listed
  Extensive experiments on four standard few-shot action benchmarks show that our method clearly outperforms previous state-of-the-art methods, with the improvement particularly significant (10+%) on the most challenging…
• Attention-Based Context Aware Reasoning for Situation Recognition
  1 Jun 2020 1 repository listed
  However, existing query-based reasoning methods have not considered handling of inter-dependent queries which is a unique requirement of semantic role prediction in SR.
• Multi-Modal Domain Adaptation for Fine-Grained Action Recognition
  27 Jan 2020 1 repository listed
  We then combine adversarial training with multi-modal self-supervision, showing that our approach outperforms other UDA methods by 3%.
• Analysis of Hand Segmentation in the Wild
  8 Mar 2018 1 repository listed
  In the quest for robust hand segmentation methods, we evaluated the performance of the state of the art semantic segmentation methods, off the shelf and fine-tuned, on existing datasets.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.