Stavros Petridis

2.4k total citations · 1 hit paper
66 papers, 1.3k citations indexed

About

Stavros Petridis is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Stavros Petridis has authored 66 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Signal Processing, 25 papers in Computer Vision and Pattern Recognition and 24 papers in Artificial Intelligence. Recurrent topics in Stavros Petridis's work include Speech and Audio Processing (44 papers), Music and Audio Processing (26 papers) and Speech Recognition and Synthesis (17 papers). Stavros Petridis is often cited by papers focused on Speech and Audio Processing (44 papers), Music and Audio Processing (26 papers) and Speech Recognition and Synthesis (17 papers). Stavros Petridis collaborates with scholars based in United Kingdom, Netherlands and Germany. Stavros Petridis's co-authors include Maja Pantić, Pingchuan Ma, Brais Martínez, Björn W. Schuller, Jie Shen, Yannis Panagakis, Anton Nijholt, Sen He, Maciej Zięba and Hatice Güneş and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Cybernetics and Pattern Recognition Letters.

In The Last Decade

Stavros Petridis

61 papers receiving 1.2k citations

Hit Papers

Diffused Heads: Diffusion Models Beat GANs on Talking-Fac... 2024 2026 2025 2024 10 20 30 40 50
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation
    2024 54 citations Stavros Petridis, Maja Pantić et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Stavros Petridis United Kingdom 19 783 483 439 317 142 66 1.3k
Athanasios Katsamanis Greece 20 667 0.9× 357 0.7× 661 1.5× 653 2.1× 221 1.6× 68 1.5k
Engin Erzin Türkiye 20 892 1.1× 657 1.4× 480 1.1× 271 0.9× 138 1.0× 112 1.5k
Panagiotis Tzirakis United Kingdom 15 492 0.6× 354 0.7× 479 1.1× 824 2.6× 152 1.1× 29 1.4k
Koichi Shinoda Japan 16 761 1.0× 331 0.7× 989 2.3× 168 0.5× 82 0.6× 136 1.4k
A. Garg United States 11 534 0.7× 504 1.0× 359 0.8× 147 0.5× 30 0.2× 16 1.0k
Werner Verhelst Belgium 16 455 0.6× 196 0.4× 345 0.8× 271 0.9× 139 1.0× 93 871
Guillaume Lathoud Switzerland 16 615 0.8× 326 0.7× 572 1.3× 96 0.3× 85 0.6× 31 1.1k
Tin Lay Nwe Singapore 18 862 1.1× 461 1.0× 613 1.4× 717 2.3× 99 0.7× 49 1.5k
Say Wei Foo Singapore 11 588 0.8× 421 0.9× 382 0.9× 589 1.9× 75 0.5× 56 1.1k
Andreas Wendemuth Germany 16 666 0.9× 233 0.5× 708 1.6× 797 2.5× 170 1.2× 107 1.3k

Countries citing papers authored by Stavros Petridis

Since Specialization
Citations

This map shows the geographic impact of Stavros Petridis's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stavros Petridis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stavros Petridis more than expected).

Fields of papers citing papers by Stavros Petridis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stavros Petridis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stavros Petridis. The network helps show where Stavros Petridis may publish in the future.

Co-authorship network of co-authors of Stavros Petridis

This figure shows the co-authorship network connecting the top 25 collaborators of Stavros Petridis. A scholar is included among the top collaborators of Stavros Petridis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stavros Petridis. Stavros Petridis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Ma, Pingchuan, et al.. (2025). Large Language Models are Strong Audio-Visual Speech Recognition Learners. 1–5. 2 indexed citations
3.
Ma, Pingchuan, et al.. (2025). Revival with Voice: Multi-modal Controllable Text-to-Speech Synthesis. 3773–3777.
4.
Ma, Pingchuan, Lu Yin, Stavros Petridis, et al.. (2024). Dynamic Data Pruning for Automatic Speech Recognition. TU/e Research Portal. 4488–4492.
5.
Petridis, Stavros, et al.. (2024). EMOPortraits: Emotion-Enhanced Multimodal One-Shot Head Avatars. 8498–8507. 5 indexed citations
6.
Kalgaonkar, Kaustubh, Niko Moritz, Pingchuan Ma, et al.. (2024). The CHiME-8 MMCSG Challenge: Multi-modal conversations in smart glasses. 7–12. 1 indexed citations
7.
Panagakis, Yannis, et al.. (2023). KAN-AV dataset for audio-visual face and speech analysis in the wild. Image and Vision Computing. 140. 104839–104839. 1 indexed citations
8.
Ma, Pingchuan, Niko Moritz, Stavros Petridis, Christian Fuegen, & Maja Pantić. (2023). Streaming Audio-Visual Speech Recognition with Alignment Regularization. 1598–1602. 2 indexed citations
9.
Wang, Yujiang, et al.. (2023). Self-supervised Video-centralised Transformer for Video Face Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(11). 1–16. 4 indexed citations
10.
Ma, Pingchuan, et al.. (2023). SparseVSR: Lightweight and Noise Robust Visual Speech Recognition. 1603–1607. 3 indexed citations
11.
Ma, Pingchuan, et al.. (2022). Speech-Driven Facial Animations Improve Speech-in-Noise Comprehension of Humans. Frontiers in Neuroscience. 15. 781196–781196. 9 indexed citations
12.
Ma, Pingchuan, Stavros Petridis, & Maja Pantić. (2022). Visual speech recognition for multiple languages in the wild. Nature Machine Intelligence. 4(11). 930–939. 85 indexed citations
13.
Ma, Pingchuan, Stavros Petridis, & Maja Pantić. (2021). Detecting Adversarial Attacks on Audiovisual Speech Recognition. 6403–6407. 6 indexed citations
14.
Ma, Pingchuan, et al.. (2021). LiRA: Learning Visual Speech Representations from Audio Through Self-Supervision. OPUS (Augsburg University). 3011–3015. 35 indexed citations
15.
Millard, David E., et al.. (2020). Domain adversarial neural networks for dysarthric speech recognition. ePrints Soton (University of Southampton). 12 indexed citations
16.
Petridis, Stavros, et al.. (2019). End-to-End Speech-Driven Realistic Facial Animation with Temporal GANs. Computer Vision and Pattern Recognition. 37–40. 20 indexed citations
17.
Petridis, Stavros, et al.. (2018). Online Attention for Interpretable Conflict Estimation in Political Debates. University of Twente Research Information. 5. 389–393. 1 indexed citations
18.
Petridis, Stavros, et al.. (2015). The MAHNOB Mimicry Database: A database of naturalistic human interactions. Pattern Recognition Letters. 66. 52–61. 35 indexed citations
19.
Petridis, Stavros, et al.. (2013). Audiovisual Detection of Laughter in Human-Machine Interaction. 129–134. 13 indexed citations
20.
Petridis, Stavros, et al.. (2012). Comparison of prediction-based fusion and feature-level fusion across different learning models. University of Twente Research Information. 813–816. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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