Charless C. Fowlkes
Biography
Charless C. Fowlkes, Ph.D., is a Full Professor in the Department of Computer Science at the University of California, Irvine, with a joint appointment in the Department of Cognitive Sciences. He is also a member of the Center for Machine Learning and Intelligent Systems, the Institute for Genomics and Bioinformatics, the Center for Complex Biological Systems, and the Center for Computational Morphodynamics. His research spans computer vision and computational biology, with a focus on perceptual grouping, image segmentation, and the application of machine learning methods to biological image analysis.
Fowlkes received the Helmholtz Prize from the International Conference on Computer Vision in 2015 for fundamental contributions to computer vision, and the Marr Prize for Best Paper at the same conference in 2009. He is a recipient of the National Science Foundation CAREER Award and has been named a Chancellor’s Fellow at UCI. His work spans a broad range of applications, from scene understanding and object detection to the construction of quantitative spatio-temporal atlases of gene expression and the mapping of peripheral neural circuits. He has served as Area Chair for the IEEE Conference on Computer Vision and Pattern Recognition, the International Conference on Computer Vision, and the European Conference on Computer Vision, and is an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence.
Fowlkes received his Ph.D. in Computer Science from the University of California, Berkeley in 2005, where he was advised by Jitendra Malik, and completed a postdoctoral fellowship jointly at Lawrence Berkeley National Laboratory and UC Berkeley. He joined the faculty at UC Irvine in 2007, where he has advised numerous graduate theses, including 12 doctoral dissertations, whose work spans computer vision, biological image analysis, and scene understanding.
Return to topEducation
- PhD in Computer Science, University of California, Berkeley, 2005
- BS in Engineering and Applied Sciences, California Institute of Technology, 2000
Distinctions
- American Statistical Association SPAIG Award, 2018
- NSF CAREER Award, 2013
- Helmholtz Prize for fundamental contributions in Computer Vision, 2015
- Marr Prize for Best Paper, Int. Conference on Computer Vision, 2009
- Chancellor's Fellow, UCI, 2019-2022
- Award for Teaching Excellence in Undergraduate Education, UCI ICS, 2014
Areas of Expertise
- Computer Vision and Perceptual Organization
- Image Segmentation and Boundary Detection
- Biological Image Analysis
- Object Detection and Scene Parsing
- 3D Human Pose Estimation
- Forensic Shoeprint Identification
- Monocular Depth Prediction
Recent Publications
- Shafique S., Kong S., Fowlkes C., “CriSp: Leveraging Tread Depth Maps for Enhanced Crime-Scene Shoeprint Matching” (opens in new tab), Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 15121 LNCS, pp. 217-235, 2025.
- Zhao Y., Ma H., Kong S., Fowlkes C., “Instance Tracking in 3D Scenes from Egocentric Videos” (opens in new tab), Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 21933-21944, 2024.
- Y. Zhao, C. Barnes, Y. Zhou, E. Shechtman, S. Amirghodsi, C. Fowlkes, “GeoFill: Reference-Based Image Inpainting of Scenes with Better Geometric Understanding” (opens in new tab), Proceedings 2023 IEEE Winter Conference on Applications of Computer Vision Wacv 2023, pp. 1776-1786, 2023. Presented at IEEE Winter Conf. on Applications of Computer Vision (WACV).
- S. Shafique, B. Kong, S. Kong, C. Fowlkes, “Creating a Forensic Database of Shoeprints from Online Shoe Tread Photos” (opens in new tab), Proceedings 2023 IEEE Winter Conference on Applications of Computer Vision Wacv 2023, pp. 858-868, 2023. Presented at IEEE Winter Conf. on Applications of Computer Vision (WACV).
- H. Li, C. Fowlkes, H. Yang, O. Dabeer, Z. Tu, S. Soatto, “Guided recommendation for model fine-tuning” (opens in new tab), Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2023-June, pp. 3633-3642, 2023. Presented at IEEE Conf. on Computer Vision and Pattern Recognition (CVPR).
- Dukler Y., Achille A., Yang H., Bowman B., Vivek V., Zancato L., Ravichandran A., Fowlkes C., Swaminathan A., Soatto S., “Your representations are in the network: composable and parallel adaptation for large scale models”, Advances in Neural Information Processing Systems, vol. 36, 2023.
- S. Punyasena, D. Haselhorst, S. Kong, C. Fowlkes, J. Moreno, “Automated identification of diverse Neotropical pollen samples using convolutional neural networks” (opens in new tab), Methods in Ecology and Evolution, vol. 13, pp. 2049-2064, 2022.
- C. Zhu, P. Rajendran, P. Hanna, I. Efimov, G. Salama, C. Fowlkes, K. Shivkumar, “High-resolution structure-function mapping of intact hearts reveals altered sympathetic control of infarct border zones” (opens in new tab), JCI Insight, vol. 7, no. 3, pp. e153913, 2022.
- Z. Wang, H. Chen, X. Li, C. Liu, Y. Xiong, J. Tighe, C. Fowlkes, “SSCAP: Self-supervised Co-occurence Action Parsing for Unsupervised Temporal Action Segmentation” (opens in new tab), Proceedings 2022 IEEE Cvf Winter Conference on Applications of Computer Vision Wacv 2022, pp. 175-184, 2022. Presented at IEEE Winter Conf. on Applications of Computer Vision (WACV).
- M. Wallingford, H. Li, A. Achille, A. Ravichandran, C. Fowlkes, R. Bhotika, S. Soatto, “Task Adaptive Parameter Sharing for Multi-Task Learning” (opens in new tab), Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2022-June, pp. 7551-7560, 2022. Presented at IEEE Conf. on Computer Vision and Pattern Recognition (CVPR).
Most Cited Publications
- P. Arbeláez, M. Maire, C. Fowlkes, J. Malik, “Contour Detection and Hierarchical Image Segmentation” (opens in new tab), IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 5, pp. 898-916, 2011.
- D. Martin, C. Fowlkes, J. Malik, “Learning to Detect Natural Image Boundaries Using Local Brightness, Color and Texture Cues” (opens in new tab), IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 5, pp. 530-549, 2004.
- C. Fowlkes, S. Belongie, F. Chung, J. Malik, “Spectral Grouping Using The Nyström Method” (opens in new tab), IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 2, pp. 214-225, 2004.
- S. Kong, X. Shen, Z. Lin, R. Mech, C. Fowlkes, “Photo Aesthetics Ranking Network with Attributes and Content Adaptation” (opens in new tab), Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 9905 LNCS, pp. 662-679, 2016. Presented at European Conf. on Computer Vision (ECCV).
- G. Ghiasi, C. Fowlkes, “Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation” (opens in new tab), Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 9907 LNCS, pp. 519-534, 2016. Presented at European Conf. on Computer Vision (ECCV).
- C. Fowlkes, C. Luengo Hendriks, S. Keränen, G. Weber, O. Rübel, M-Y Huang, S. Chatoor, A. DePace, L. Simirenko, C. Henriquez, A. Beaton, R. Weiszmann, S. Celniker, B. Hamann, D. Knowles, M. Biggin, M. Eisen, J. Malik, “A quantitative spatio-temporal atlas of gene expression in the Drosophila blastoderm” (opens in new tab), Cell, vol. 133, no. 2, pp. 364-374, 2008.
- X. Zhu, C. Vondrick, C. Fowlkes, D. Ramanan, “Do we need more training data?” (opens in new tab), International Journal of Computer Vision, vol. 119, pp. 1-17, 2015.
- C. Desai, D. Ramanan, C. Fowlkes, “Discriminative Models for Multi-class Object Layout” (opens in new tab), International Journal of Computer Vision, vol. 95, no. 1, pp. 1-12, 2011.
- D. Park, D. Ramanan, C. Fowlkes, “Multiresolution models for object detection” (opens in new tab), Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 6314 LNCS, pp. 241-254, 2010. Presented at Proc. European Conf. on Computer Vision (ECCV).
- C. Fowlkes, D. Martin, J. Malik, “Local Figure/Ground Cues are Valid for Natural Images” (opens in new tab), Journal of Vision, vol. 7, no. 8, pp. 1-9, 2007.
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Last updated on 11/14/2026.