Temporal Action Segmentation: An Analysis of Modern Techniques
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Abstract (arXiv)
Temporal action segmentation (TAS) in videos aims at densely identifying video frames in minutes-long videos with multiple action classes. As a long-range video understanding task, researchers have developed an extended collection of methods and examined their performance using various benchmarks. Despite the rapid growth of TAS techniques in recent years, no systematic survey has been conducted in these sectors. This survey analyzes and summarizes the most significant contributions and trends. In particular, we first examine the task definition, common benchmarks, types of supervision, and prevalent evaluation measures. In addition, we systematically investigate two essential techniques of this topic, i.e., frame representation and temporal modeling, which have been studied extensively in the literature. We then conduct a thorough review of existing TAS works categorized by their levels of supervision and conclude our survey by identifying and emphasizing several research gaps. In addition, we have curated a list of TAS resources, which is available at https://github.com/nus-cvml/awesome-temporal-action-segmentation.
Key facts. Cited by 85 papers in the map (data through 14 Oct 2026). Builds on 122 of its 206 references that are in the map. First posted on arXiv 19 Oct 2022.
Builds on
122 of 206 references.
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50 most cited of 122 All 122 (JSON)
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Citing papers per year: 2023: 15; 2024: 19; 2025: 36; 2026: 15.
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- 2026Unsupervised Skeleton-Based Action Segmentation via Hierarchical Spatiotemporal Vector Quantization16 Apr 2026
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- 2025FALCONEye: Finding Answers and Localizing Content in ONE-hour-long videos with multi-modal LLMscited by 0
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- 2026Exploring Vision-Language Models for Open-Vocabulary Zero-Shot Action Segmentation24 Feb 2026
- 2025Building Egocentric Procedural AI Assistant: Methods, Benchmarks, and Challenges17 Nov 2025
- 2025EgoInstruct: An Egocentric Video Dataset of Face-to-face Instructional Interactions with Multi-modal LLM Benchmarking26 Sep 2025
- 2025FALCONEye: Finding Answers and Localizing Content in ONE-hour-long videos with multi-modal LLMs25 Mar 2025
- 2025Visual Large Language Models for Generalized and Specialized Applications6 Jan 2025
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- 2023DiffAnt: Diffusion Models for Action Anticipationcited by 9
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- 2023DiffAnt: Diffusion Models for Action Anticipation27 Nov 2023
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- 2024HIMO: A New Benchmark for Full-Body Human Interacting with Multiple Objectscited by 36
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- 2023Every Mistake Counts in Assemblycited by 18
- 2023Permutation-Aware Action Segmentation via Unsupervised Frame-to-Segment Alignmentcited by 17
- 2023Synchronization is All You Need: Exocentric-to-Egocentric Transfer for Temporal Action Segmentation with Unlabeled Synchronized Video Pairscited by 17
- 2023OTAS: Unsupervised Boundary Detection for Object-Centric Temporal Action Segmentationcited by 11
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- 2026D-CLOT: Double Closed Loop Optimal Transport for Unsupervised Action Segmentation6 Aug 2026
- 2026Adaptive Latent Trajectory Anchoring for Action Segmentation Dataset Condensation10 Jul 2026
- 2026AI-Assisted Competency Assessment from Egocentric Video in Simulation-Based Nursing Education16 May 2026
- 2026Jointly Learning Structured Representations and Stabilized Affinity for Human Motion Segmentation7 May 2026
- 2026All Eyes on the Workflow: Automated and Efficient Event Discovery from Video Streams24 Apr 2026
- 2026Deep kernel video approximation for unsupervised action segmentation23 Apr 2026
- 2026Unsupervised Skeleton-Based Action Segmentation via Hierarchical Spatiotemporal Vector Quantization16 Apr 2026
- 2026Boundary-Centric Clip-Budgeted Active Learning for Temporal Action Segmentation16 Apr 2026
- 2026Spectral Scalpel: Amplifying Adjacent Action Discrepancy via Frequency-Selective Filtering for Skeleton-Based Action Segmentation25 Mar 2026
- 2026ENIGMA-360: An Ego-Exo Dataset for Human Behavior Understanding in Industrial Scenarios10 Mar 2026
- 2026Hierarchical Action Learning for Weakly-Supervised Action Segmentation27 Feb 2026
12 newest of 74 All 74 (JSON)