World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
9756
World Ranking
7867
National Ranking
64

Overview

Esa Rahtu is affiliated with Tampere University in Finland. Their research primarily focuses on computer science and engineering, with a strong emphasis on computer vision and pattern recognition. Their body of work spans numerous subfields including aerospace engineering, signal processing, artificial intelligence, and media technology.

The scientist's research covers a variety of main topics such as advanced vision and imaging, robotics and sensor-based localization, advanced neural network applications, advanced image processing techniques, advanced image and video retrieval techniques, speech and audio processing, and music and audio processing.

Some of their recent papers include:

  • OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose Estimation, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • HybVIO: Pushing the Limits of Real-time Visual-inertial Odometry, 2022, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • Visually Guided Sound Source Separation and Localization using Self-Supervised Motion Representations, 2022, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • Boosting Monocular Depth Estimation with Lightweight 3D Point Fusion, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Taming Visually Guided Sound Generation, 2021, arXiv (Cornell University)

Frequent co-authors in their research include:

  • Janne Heikkilä
  • Juho Kannala
  • Lam Huynh
  • Jiřı́ Matas
  • Lingyu Zhu

The main venues where Esa Rahtu has published their work include:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
  • 2021 International Conference on 3D Vision (3DV)

The scientist has contributed extensively to the domains of advanced vision systems and robotics localization, employing techniques rooted in neural networks and signal processing to advance understanding in these areas. Their research addresses challenges in both visual and audio data processing, covering sound source separation, generation, and related audio technologies.

Best Publications

  • Fine-Grained Visual Classification of Aircraft

    Subhransu Maji;Esa Rahtu;Juho Kannala;Matthew B. Blaschko

  • BSIF: Binarized statistical image features

    Juho Kannala;Esa Rahtu

  • Segmenting salient objects from images and videos

    Esa Rahtu;Juho Kannala;Mikko Salo;Janne Heikkilä

  • Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach

    Aleksei Tiulpin;Jérôme Thevenot;Esa Rahtu;Petri Lehenkari

  • Recognition of blurred faces using Local Phase Quantization

    T. Ahonen;E. Rahtu;V. Ojansivu;J. Heikkila

  • Siamese network features for image matching

    Iaroslav Melekhov;Juho Kannala;Esa Rahtu

  • Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data.

    Aleksei Tiulpin;Aleksei Tiulpin;Stefan Klein;Sita M. A. Bierma-Zeinstra;Jérôme Thevenot

  • Fast and efficient saliency detection using sparse sampling and kernel density estimation

    Hamed Rezazadegan Tavakoli;Esa Rahtu;Janne Heikkilä

  • Learning a category independent object detection cascade

    Esa Rahtu;Juho Kannala;Matthew Blaschko

  • Image-Based Localization Using Hourglass Networks

    Iaroslav Melekhov;Juha Ylioinas;Juho Kannala;Esa Rahtu

  • Generating Object Segmentation Proposals Using Global and Local Search

    Pekka Rantalankila;Juho Kannala;Esa Rahtu

  • Relative Camera Pose Estimation Using Convolutional Neural Networks

    Iaroslav Melekhov;Juha Ylioinas;Juho Kannala;Esa Rahtu

  • Identification of tumor epithelium and stroma in tissue microarrays using texture analysis

    Nina Linder;Juho Konsti;Riku Turkki;Riku Turkki;Esa Rahtu

  • Multi-Modal Dense Video Captioning

    Vladimir Iashin;Esa Rahtu

  • Rotation invariant local phase quantization for blur insensitive texture analysis

    V. Ojansivu;E. Rahtu;J. Heikkila

  • Rethinking the Evaluation of Video Summaries

    Mayu Otani;Yuta Nakashima;Esa Rahtu;Janne Heikkila

  • A malaria diagnostic tool based on computer vision screening and visualization of Plasmodium falciparum candidate areas in digitized blood smears.

    Nina Linder;Riku Turkki;Margarita Walliander;Andreas Mårtensson

  • Affine invariant pattern recognition using multiscale autoconvolution

    E. Rahtu;M. Salo;J. Heikkila

  • Video Summarization Using Deep Semantic Features

    Mayu Otani;Yuta Nakashima;Esa Rahtu;Janne Heikkilä

  • TriCoS: a tri-level class-discriminative co-segmentation method for image classification

    Yuning Chai;Esa Rahtu;Victor Lempitsky;Luc Van Gool

  • Guiding Monocular Depth Estimation Using Depth-Attention Volume

    Lam Huynh;Phong Nguyen-Ha;Jiri Matas;Esa Rahtu

Frequent Co-Authors

Janne Heikkilä
Janne Heikkilä University of Oulu
Juho Kannala
Juho Kannala Aalto University
Simo Saarakkala
Simo Saarakkala University of Oulu
Jiri Matas
Jiri Matas Czech Technical University in Prague
Miska Hannuksela
Miska Hannuksela Nokia (Finland)
Ali Borji
Ali Borji Quintic AI
Naokazu Yokoya
Naokazu Yokoya Nara Institute of Science and Technology
Matti Pietikäinen
Matti Pietikäinen University of Oulu
Andrea Vedaldi
Andrea Vedaldi University of Oxford

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring related online degrees can help tailor your educational journey in Computer Science based on your career goals and budget. Many students look for programs that offer flexibility, affordability, and direct career benefits. If you’re interested in advancing your knowledge without incurring large debts, consider these inexpensive masters degrees in various tech-related fields, which can open doors to specialist and management roles in the industry.

Some professionals aiming for leadership roles may want to pursue an online doctorate in organizational leadership, perfect for those interested in integrating technology with organizational change and management. Alternatively, if you’re seeking an accessible option to quickly enter the workforce, check out the easiest associate's degree to get for fields related to computing, IT, or even business administration.

For educators considering technology-focused leadership roles, exploring an online edd can lead to dynamic opportunities in academic and administrative settings. No matter your background or aspirations, these degree pathways can complement your computer science studies and pave versatile career trails.

Best Scientists Citing Esa Rahtu

Trending Scientists

Recently Published Articles