World's Best Scientists 2026 revealed!
Tatsuya Harada

Tatsuya Harada

Award Badge
Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
48
Citations
11839
World Ranking
6095
National Ranking
85

Research.com Recognitions

  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award

Overview

Tatsuya Harada is affiliated with the University of Tokyo in Japan. Their research spans multiple areas within computer science, particularly focusing on computer vision and pattern recognition.

The scientist's work covers key subfields including:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Signal Processing
  • Computational Mechanics

Main topics explored in their research include:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Image and Video Retrieval Techniques
  • Advanced Vision and Imaging
  • Human Pose and Action Recognition
  • 3D Shape Modeling and Analysis
  • Radiomics and Machine Learning in Medical Imaging

Recent publications of note from Tatsuya Harada include:

  • "Domain Generalization Using a Mixture of Multiple Latent Domains," 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Lepard: Learning partial point cloud matching in rigid and deformable scenes," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Frequency-Aware Feature Fusion for Dense Image Prediction," 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction," 2022, arXiv (Cornell University)

Frequent coauthors working with Tatsuya Harada include:

  • Yusuke Mukuta
  • Lin Gu
  • Ziteng Cui
  • Yusuke Kurose

The primary venues where Tatsuya Harada has published include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Medical Image Analysis
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

The body of work shows a concentration on developing methods for image analysis, domain adaptation, and multimodal learning, with applications extending to medical imaging and 3D modeling. The range of publication venues and collaborations indicate active engagement in key research communities focused on computer vision and artificial intelligence.

Best Publications

  • Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

    Kuniaki Saito;Kohei Watanabe;Yoshitaka Ushiku;Tatsuya Harada

  • Neural 3D Mesh Renderer

    Hiroharu Kato;Yoshitaka Ushiku;Tatsuya Harada

  • Strong-Weak Distribution Alignment for Adaptive Object Detection

    Kuniaki Saito;Yoshitaka Ushiku;Tatsuya Harada;Kate Saenko

  • MFNet: Towards real-time semantic segmentation for autonomous vehicles with multi-spectral scenes

    Qishen Ha;Kohei Watanabe;Takumi Karasawa;Yoshitaka Ushiku

  • Open Set Domain Adaptation by Backpropagation

    Kuniaki Saito;Shohei Yamamoto;Yoshitaka Ushiku;Tatsuya Harada

  • Asymmetric tri-training for unsupervised domain adaptation

    Kuniaki Saito;Yoshitaka Ushiku;Tatsuya Harada

  • Domain Generalization Using a Mixture of Multiple Latent Domains

    Toshihiko Matsuura;Tatsuya Harada

  • Adversarial Dropout Regularization

    Kuniaki Saito;Yoshitaka Ushiku;Tatsuya Harada;Kate Saenko

  • Learning environmental sounds with end-to-end convolutional neural network

    Yuji Tokozume;Tatsuya Harada

  • Learning from Between-class Examples for Deep Sound Recognition

    Yuji Tokozume;Yoshitaka Ushiku;Tatsuya Harada

  • Between-Class Learning for Image Classification

    Yuji Tokozume;Yoshitaka Ushiku;Tatsuya Harada

  • Lepard: Learning partial point cloud matching in rigid and deformable scenes

    Unknown

  • Image Generation from Small Datasets via Batch Statistics Adaptation

    Atsuhiro Noguchi;Tatsuya Harada

  • Multispectral Object Detection for Autonomous Vehicles

    Karasawa Takumi;Kohei Watanabe;Qishen Ha;Antonio Tejero-De-Pablos

  • Goal-Oriented Gaze Estimation for Zero-Shot Learning

    Yang Liu;Lei Zhou;Xiao Bai;Yifei Huang

  • Multitask AET With Orthogonal Tangent Regularity for Dark Object Detection

    Ziteng Cui;Guo-Jun Qi;Lin Gu;Shaodi You

  • Online growing neural gas for anomaly detection in changing surveillance scenes

    Qianru Sun;Hong Liu;Tatsuya Harada

  • Discriminative spatial pyramid

    Tatsuya Harada;Yoshitaka Ushiku;Yuya Yamashita;Yasuo Kuniyoshi

  • Portable absolute orientation estimation device with wireless network under accelerated situation

    T. Harada;H. Uchino;T. Mori;T. Sato

  • Portable orientation estimation device based on accelerometers, magnetometers and gyroscope sensors for sensor network

    T. Harada;H. Uchino;T. Mori;T. Sato

  • Image Reconstruction from Bag-of-Visual-Words

    Hiroharu Kato;Tatsuya Harada

  • Learning View Priors for Single-View 3D Reconstruction

    Hiroharu Kato;Tatsuya Harada

Frequent Co-Authors

Yasuo Kuniyoshi
Yasuo Kuniyoshi University of Tokyo
Toru Sato
Toru Sato Kyoto University
Kate Saenko
Kate Saenko Boston University
Jun Zhou
Jun Zhou Griffith University
Emanuele Rodolà
Emanuele Rodolà Sapienza University of Rome
Daniel Cremers
Daniel Cremers Technical University of Munich
Luc Van Gool
Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)
Heng Tao Shen
Heng Tao Shen University of Electronic Science and Technology of China
Yang Yang
Yang Yang University of Electronic Science and Technology of China
Stephen Lin
Stephen Lin Microsoft Research Asia (China)

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