Scholar4AI Updated 2026-11-04 18:03 UTC+09:00

Action recognition (Kinetics, UCF101, HMDB51)

Browse dataset profiles

data category: Face, person and video benchmarks · 0 papers in the last 7 days

← Most-used data · All Face, person and video benchmarks datasets

Faces, people, poses, facial expressions and human actions in images and video.

Share: X LinkedIn Bluesky Threads Facebook Reddit Hacker News Hatena LINE Email
Copy:

Names searched for: Kinetics-400, Kinetics-600, Kinetics-700, UCF101, UCF-101, HMDB51, HMDB-51, Something-Something, ActivityNet

Key findings#

  • From Nov 2023 to Oct 2026, 198 archived papers mentioned Action recognition (Kinetics, UCF101, HMDB51) in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jan 2026 (13).
  • Action recognition (Kinetics, UCF101, HMDB51) was mentioned in 4 papers in the last 30 days (2026-10-06 to 2026-11-04), ranking #84 of the 255 datasets mentioned.
  • By journal category: AI (4).
  • Most of them appeared in Pattern Recognition (2), International Journal of Computer Vision (1) and Expert Systems with Applications (1).
  • From 2017 to 2026 (so far), Action recognition (Kinetics, UCF101, HMDB51) was mentioned in 290 papers in the tracked journals, most of them in AI (288), economics (1) and information systems (1).
  • 69 of them were published in 2025, against 9 in 2017.
  • Since 2023, the institutions with the most of these papers were Chinese Academy of Sciences (17), Shanghai Artificial Intelligence Laboratory (12) and Peking University (11).
  • The journals publishing most of them were IEEE Transactions on Pattern Analysis and Machine Intelligence (54), International Journal of Computer Vision (54) and Pattern Recognition (15).
  • The most-cited of them is “Vision-Language Models for Vision Tasks: A Survey” (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024), with 998 citations.
  • Papers use Action recognition (Kinetics, UCF101, HMDB51) most often with ImageNet (90), YouTube / TikTok (50) and MS COCO (34); it has 31 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

Mentions over 36 months#

Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
TrendNov 23–Oct 24Nov 24–Oct 25Nov 25–Oct 2636 months
617166198

Papers per year#

2017: 9 papers2018: 6 papers2019: 7 papers2020: 17 papers2021: 16 papers2022: 19 papers2023: 30 papers2024: 60 papers2025: 69 papers2026 (so far): 57 papers
20172026 (so far)
Papers per publication year and category
Category2017201820192020202120222023202420252026 (so far)
AI96717161930606955
Economics0000000001
Information Systems0000000001
All categories96717161930606957

Where the papers come from#

Countries with the most papers, since 2023
#CountryPapers
1China129
2United States32
3United Kingdom28
4Australia26
5Singapore20
6Hong Kong16
7India10
8France8
9Italy7
10South Korea6
Keywords with the most papers, since 2023
#KeywordPapers
1human action recognition21
2vision-language models21
3CLIP18
4video action recognition17
5UCF10113
6multimodal fusion13
7HMDB5111
8video classification10
9attention mechanism9
10domain generalization9

Most-cited papers#

Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.

Used together with#

Papers use Action recognition (Kinetics, UCF101, HMDB51) most often with ImageNet (90), YouTube / TikTok (50) and MS COCO (34); it has 31 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST. The whole network →

What papers use Action recognition (Kinetics, UCF101, HMDB51) together with (at least 3 papers; lift 1 = chance)
Used withTypePapers using bothLift
ImageNetDataset906.3
YouTube / TikTokDataset504.5
MS COCODataset346.0
Caltech-101 / 256Dataset2426.8
CIFAR-10 / CIFAR-100Dataset182.1
Fine-grained benchmarks (CUB-200, Stanford Cars, Oxford Flowers)Dataset1712.2
Skeleton and pose (NTU RGB+D, Human3.6M)Dataset1717.5
AudioSet / ESC-50Dataset1137.0
MNIST / Fashion-MNISTDataset111.6
PASCAL VOCDataset115.5
CityscapesDataset95.0
FacebookDataset80.4
Papers mentioning Action recognition (Kinetics, UCF101, HMDB51) in the last 30 days, newest first.
DateTitleJournalAuthorsAffiliations
2026-10-26TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and GenerationInternational Journal of Computer VisionHaokun Lin, Teng Wang, Yixiao Ge et al.City University of Hong Kong; Chinese Academy of Sciences; Tencent (China); …
2026-10-24Single-stage Temporal Action Detection with Coarse-to-Fine Auxiliary Supervision and asymmetric boundary priorPattern RecognitionXianhua Zeng, SiQi Zhou, XinYu LiuChongqing University of Posts and Telecommunications
2026-10-23EMM-CVT: An Efficient Multi-Modal Vision Transformer for compressed video action recognitionPattern RecognitionHong Wen, Bing Li, Liang Qian et al.Beijing Jiaotong University; Nankai University
2026-10-06CRAFMark: Contrastive-driven robust adaptive frequency-aware video watermarking against H.265/HEVC compressionExpert Systems with ApplicationsShunzhe Zhu, Ke Niu, Jun Li et al.Chinese People's Armed Police Force Engineering University
Cite this page

Scholar4AI. (2026). Action recognition (Kinetics, UCF101, HMDB51). Journal and Conference Research Rankings. Retrieved November 4, 2026, from https://scholar4ai.com/datasets/action-recognition-kinetics-ucf101-hmdb51

@misc{scholar4ai-datasets-action-recognition-kinetics-ucf101-hmdb51,
  author = {{Scholar4AI}},
  title = {Action recognition (Kinetics, UCF101, HMDB51)},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/action-recognition-kinetics-ucf101-hmdb51}},
  urldate = {2026-11-04},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).