Teófilo de Campos

2.1k citations
43 papers · 819 indexed · h-index 12

Teófilo de Campos

40 papers receiving 772 citations

Peers

Teófilo de Campos
Comparison fields: 5 of 95
  • Computer Vision and Pattern Recognition 603
  • Human-Computer Interaction 87
  • Media Technology 126
  • Signal Processing 87
  • Artificial Intelligence 233
Replace Alessandro Bissacco with:
Alessandro Bissacco United States
Anoop Namboodiri India
Chunxiao Fan China
Dehui Kong China
Elsayed E. Hemayed Egypt
Jamshid Shanbehzadeh Iran
Hefei Ling China
Yansong Tang China
Teófilo de Campos relative to Alessandro Bissacco United States Alessandro Bissacco's profile →
Citations per field
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Citations per year

Countries citing papers authored by Teófilo de Campos

Since Specialization
Citations

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

Fields of papers citing papers by Teófilo de Campos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Teófilo de Campos. 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 Teófilo de Campos. The network helps show where Teófilo de Campos may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Teófilo de Campos, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Teófilo de Campos Line = papers co-authored together Teófilo de Campos links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20221
2 20225
3
VICTOR: a Dataset for Brazilian Legal Documents Classification.
202030
4 20204
5 20206
6
EdgeNet: Semantic Scene Completion from RGB-D images.
201911
7 20190
8 20163
9 20160
10
A Listener Position Adaptive Stereo System for Object-Based Reproduction
20157
11 20154
12 20144
13 201336
14
Domain Adaptation in the Context of Sport Video Action Recognition
20117
15 201140
16 20104
17
CHARACTER RECOGNITION IN NATURAL IMAGES
2009298
18
Prediction of relevance of an image from a scan pattern
20081
19 20063
20 200210

About Teófilo de Campos

Teófilo de Campos is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Signal Processing, having authored 43 papers that have together received 819 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (10 papers), Advanced Image and Video Retrieval Techniques (8 papers), Video Surveillance and Tracking Methods (7 papers), Advanced Vision and Imaging (6 papers), Image Retrieval and Classification Techniques (6 papers), Robotics and Sensor-Based Localization (5 papers), Speech and Audio Processing (5 papers) and Hand Gesture Recognition Systems (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (603 citations), Human-Computer Interaction (87 citations) and Media Technology (126 citations). Teófilo de Campos has collaborated with scholars based in United Kingdom, Brazil and France. Frequent co-authors include Manik Varma, Josef Kittler, Florent Perronnin, David W. Murray, Jorge Sánchez, Adrian Hilton, William Christmas, David Windridge, Moacir Antonelli Ponti and Arto Klami. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Pattern Recognition Letters.

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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