Lluís Gómez

4.3k total citations · 2 hit papers
26 papers, 2.2k citations indexed

About

Lluís Gómez is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Lluís Gómez has authored 26 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 4 papers in Media Technology. Recurrent topics in Lluís Gómez's work include Handwritten Text Recognition Techniques (22 papers), Advanced Image and Video Retrieval Techniques (10 papers) and Image Retrieval and Classification Techniques (9 papers). Lluís Gómez is often cited by papers focused on Handwritten Text Recognition Techniques (22 papers), Advanced Image and Video Retrieval Techniques (10 papers) and Image Retrieval and Classification Techniques (9 papers). Lluís Gómez collaborates with scholars based in Spain, Japan and Italy. Lluís Gómez's co-authors include Dìmosthenis Karatzas, Masakazu Iwamura, Seiichi Uchida, Faisal Shafait, Anguelos Nicolaou, Jon Almazán, Joan Mas, David Mota, Lluís-Pere de las Heras and Andrew D. Bagdanov and has published in prestigious journals such as Pattern Recognition, Pattern Recognition Letters and Multimedia Tools and Applications.

In The Last Decade

Lluís Gómez

25 papers receiving 2.1k citations

Hit Papers

align trajectories

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.

ICDAR 2015 competition on Robust Reading

2015 874 citations Dìmosthenis Karatzas, Lluís Gómez et al. Florence Research (University of Florence) profile →
ICDAR 2013 Robust Reading Competition

2013 800 citations Dìmosthenis Karatzas, Faisal Shafait et al. UWA Profiles and Research Repository (UWA) profile →

Peers

Lluís Gómez

CVPR

MT

AI

HI

IS

Pengyuan Lyu China

Jon Almazán Spain

Canjie Luo China

Hwalsuk Lee South Korea

Ergina Kavallieratou Greece

Satoshi Naoi Japan

Christian Viard-Gaudin France

Mohammad Tanvir Parvez Saudi Arabia

Marçal Rusiñol Spain

Ihsin T. Phillips United States

Pengyuan Lyu China

Lluís Gómez

1.4k ×0.7

CVPR

529 ×0.6

MT

305 ×0.7

AI

28 ×0.5

HI

35 ×0.6

IS

Citations per year, relative to Lluís Gómez Lluís Gómez (= 1×) peers Pengyuan Lyu

Countries citing papers authored by Lluís Gómez

Since Specialization

Citations

This map shows the geographic impact of Lluís Gómez'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 Lluís Gómez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lluís Gómez more than expected).

Fields of papers citing papers by Lluís Gómez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lluís Gómez. 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 Lluís Gómez. The network helps show where Lluís Gómez may publish in the future.

Co-authorship network of co-authors of Lluís Gómez

This figure shows the co-authorship network connecting the top 25 collaborators of Lluís Gómez. A scholar is included among the top collaborators of Lluís Gómez 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 Lluís Gómez. Lluís Gómez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Kang, Lei, et al.. (2025). Preserving privacy without compromising accuracy: Machine unlearning for handwritten text recognition. Pattern Recognition. 172. 112411–112411.

2.

Bagdanov, Andrew D., et al.. (2025). EUFCC-340K: A faceted hierarchical dataset for metadata annotation in GLAM collections. Multimedia Tools and Applications. 84(32). 39259–39282. 1 indexed citations

3.

Nguyen, Khanh, et al.. (2023). Show, Interpret and Tell: Entity-Aware Contextualised Image Captioning in Wikipedia. Proceedings of the AAAI Conference on Artificial Intelligence. 37(2). 1940–1948. 1 indexed citations

4.

Biswas, Sanket, Ali Furkan Biten, Alícia Fornés, et al.. (2023). Text-DIAE: A Self-Supervised Degradation Invariant Autoencoder for Text Recognition and Document Enhancement. Proceedings of the AAAI Conference on Artificial Intelligence. 37(2). 2330–2338. 15 indexed citations

5.

Biten, Ali Furkan, et al.. (2022). Is An Image Worth Five Sentences? A New Look into Semantics for Image-Text Matching. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 2483–2492. 13 indexed citations

6.

Mathew, Minesh, et al.. (2020). RoadText-1K: Text Detection & Recognition Dataset for Driving Videos. 11074–11080. 20 indexed citations

7.

Dey, Sounak, et al.. (2020). Real-time Lexicon-free Scene Text Retrieval. Pattern Recognition. 110. 107656–107656. 13 indexed citations

8.

Gómez, Lluís, Marçal Rusiñol, & Dìmosthenis Karatzas. (2018). Cutting Sayre's Knot: Reading Scene Text without Segmentation. Application to Utility Meters. 97–102. 22 indexed citations

9.

Gómez, Lluís, Anguelos Nicolaou, & Dìmosthenis Karatzas. (2017). Improving patch-based scene text script identification with ensembles of conjoined networks. Pattern Recognition. 67. 85–96. 58 indexed citations

10.

Gómez, Lluís & Dìmosthenis Karatzas. (2017). TextProposals: A text-specific selective search algorithm for word spotting in the wild. Pattern Recognition. 70. 60–74. 76 indexed citations

11.

Nicolaou, Anguelos, et al.. (2017). FAST: Facilitated and Accurate Scene Text Proposals through FCN Guided Pruning. Pattern Recognition Letters. 119. 112–120. 13 indexed citations

12.

Gómez, Lluís, Marçal Rusiñol, & Dìmosthenis Karatzas. (2017). LSDE: Levenshtein Space Deep Embedding for Query-by-String Word Spotting. 499–504. 12 indexed citations

13.

Gómez, Lluís & Dìmosthenis Karatzas. (2016). A Fine-Grained Approach to Scene Text Script Identification. 192–197. 33 indexed citations

14.

Gómez, Lluís. (2016). Exploiting similarity hierarchies for multi-script scene text understanding. Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona). 1 indexed citations

15.

Gómez, Lluís & Dìmosthenis Karatzas. (2016). A fast hierarchical method for multi-script and arbitrary oriented scene text extraction. International Journal on Document Analysis and Recognition (IJDAR). 19(4). 335–349. 24 indexed citations

16.

Nicolaou, Anguelos, Andrew D. Bagdanov, Lluís Gómez, & Dìmosthenis Karatzas. (2016). Visual Script and Language Identification. Florence Research (University of Florence). 15 indexed citations

17.

Karatzas, Dìmosthenis, Lluís Gómez, Anguelos Nicolaou, et al.. (2015). ICDAR 2015 competition on Robust Reading. Florence Research (University of Florence). 1156–1160. 874 indexed citations breakdown →

18.

Gómez, Lluís & Dìmosthenis Karatzas. (2014). MSER-Based Real-Time Text Detection and Tracking. 3110–3115. 47 indexed citations

19.

Karatzas, Dìmosthenis, Faisal Shafait, Seiichi Uchida, et al.. (2013). ICDAR 2013 Robust Reading Competition. UWA Profiles and Research Repository (UWA). 1484–1493. 800 indexed citations breakdown →

20.

Gómez, Lluís & Dìmosthenis Karatzas. (2013). Multi-script Text Extraction from Natural Scenes. 467–471. 72 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.

Explore authors with similar magnitude of impact