| Robotics Institute |
Carnegie Mellon University |
3D reconstruction, autonomous systems, medical imaging |
Link |
| Computer Science and AI Laboratory (CSAIL) |
MIT |
Object recognition, scene understanding, foundational work with faculty like Antonio Torralba |
Link |
| Stanford AI Lab (SAIL) and Vision Lab |
Stanford University |
Pioneering work in deep learning for vision, including Fei-Fei Li's ImageNet project |
Link |
| Berkeley Artificial Intelligence Research (BAIR) |
UC Berkeley |
Applications in robotics and augmented reality, segmentation, motion analysis |
Link |
| Computer Vision Group |
University of Toronto |
Neural networks, strong ties to the Vector Institute |
Link |
| Computer Vision Lab |
ETH Zurich |
Drone navigation, biomedical imaging, engineering applications |
Link |
| Computational and Biological Learning (CBL) |
Cambridge University |
Machine learning for vision, with researchers like Ghahramani, Rasmussen, Turner |
Link |
| Gatsby Unit |
University College London (UCL) |
Statistical machine learning and neuroscience approaches to vision |
Link |
| Computer Vision Group |
MPI Tübingen |
Core vision problems and biological vision systems |
Link |
| Amsterdam Machine Learning Lab (AMLab) |
University of Amsterdam |
Led by Max Welling, focuses on deep generative models |
Link |
| Bayesian and Neural Systems |
University of Edinburgh |
Probabilistic methods and deep learning for vision |
Link |
| Machine Intelligence Group |
University of Edinburgh |
Computer vision and machine learning integration |
Link |
| Computer Vision Group |
Imperial College London |
Medical image analysis and general vision problems |
Link |
| Visual Geometry Group (VGG) |
University of Oxford |
Geometric approaches to vision problems, renowned for VGGNet |
Link |
| Applied and Theoretical ML Group |
University of Oxford |
Uncertainty in deep learning for vision, led by Yarin Gal |
Link |
| Dalle Molle Institute (IDSIA) |
USI-SUPSI, Lugano |
Neural networks for vision, led by Jürgen Schmidhuber |
Link |
| SIERRA Team |
ENS, INRIA Paris |
Statistical machine learning for vision applications |
Link |
| Machine Learning Group |
Technical University Berlin |
SVMs, neural networks, kernel methods for vision |
Link |
| Computer Vision Group |
Stony Brook University |
Ranked in top 10 nationally, focuses on various vision tasks |
Link |
| Optimization for Vision and Learning |
University of Oxford |
Optimization methods for vision problems, led by M. Pawan Kumar |
Link |
| Mila |
University of Montreal |
Deep learning for vision, led by Yoshua Bengio |
Link |
| Computational Vision Lab |
Caltech |
Visual recognition and human visual system modeling |
Link |
| UCLA Vision Lab |
UCLA |
Image analysis and understanding, video interpretation |
Link |
| CI2CV Lab |
Various Affiliations |
Mobile computer vision, model-based vision, alignment and learning |
Link |
| Computer Vision Center (CVC) |
Universitat Autònoma de Barcelona |
Document analysis, medical imaging, intelligent transportation |
Link |
| Willow Team |
INRIA Paris |
Large-scale visual recognition and scene understanding |
Link |
| GRAIL |
University of Washington |
Graphics and imaging applications for computer vision |
Link |
| Computer Vision Group |
TU Munich |
3D reconstruction, autonomous navigation, medical imaging |
Link |
| Computer Vision Group |
University of Illinois at Urbana-Champaign |
Object recognition, scene understanding, activity recognition |
Link |
| Multimedia Laboratory |
The Chinese University of Hong Kong |
Image/video analysis, deep learning for vision |
Link |
| Computer Vision Lab |
KAIST |
Visual recognition, 3D vision, medical imaging |
Link |
| Computer Vision Lab |
Seoul National University |
Scene understanding, visual recognition |
Link |
| Australian Institute for Machine Learning |
University of Adelaide |
Visual recognition, medical imaging, surveillance |
Link |
| Computer Vision Laboratory |
University of Maryland |
Object recognition, scene understanding, video analysis |
Link |
| Toyota Technological Institute |
Chicago |
Vision algorithms for autonomous systems |
Link |
| Computer Vision Group |
University of Michigan |
3D reconstruction, object recognition, medical imaging |
Link |
| Computer Vision Group |
Cornell University |
Scene understanding, activity recognition |
Link |
| Visual Computing Group |
Harvard University |
Graphics and vision integration |
Link |
| Computer Vision Laboratory |
Columbia University |
3D modeling, motion analysis, object recognition |
Link |
| Computer Vision and Active Perception Lab |
KTH Royal Institute of Technology |
Robotics vision, human-computer interaction |
Link |
| Center for Research in Computer Vision |
University of Central Florida |
Action recognition, anomaly detection, surveillance |
Link |
| Computer Vision Lab |
Penn State University |
Medical imaging, biometrics, surveillance |
Link |
| Vision, Dynamics and Learning Lab |
Johns Hopkins University |
Motion analysis, medical imaging |
Link |
| Image Processing Group |
Heidelberg University |
3D reconstruction, biomedical imaging |
Link |
| Visual Computing Group |
University of Bath |
Graphics and vision integration, AR/VR |
Link |
| Image and Vision Computing Group |
University of Warwick |
Medical imaging, industrial inspection |
Link |
| Machine Intelligence Lab |
University of Cambridge |
Probabilistic models for vision, led by Zoubin Ghahramani |
Link |
| Computer Vision Lab |
National University of Singapore |
Scene understanding, 3D reconstruction |
Link |
| Computational Perception Lab |
Georgia Tech |
Human-centered perception systems |
Link |
| Vision and AI Lab (VAL) |
Indian Institute of Science Bangalore |
Computer Vision and ML |
Link |
| Image Processing and Computer Vision (IPCV) Lab |
Indian Institute of Technology Madras |
Multi-Modal CV, 3D Recovery and Image Synthesis |
Link |