Khan, Fahad Shahbaz

Transformers in Vision: A Survey

Khan, S., Naseer, M., Hayat, M., Zamir, S. W., Khan, F. S., & Shah, M. (2022) · ACM Computing Surveys

Advanced Neural Network ApplicationsMultimodal Machine Learning Applications

Cited by 3,595

Transformers in Vision: A Survey

Khan, S., Naseer, M., Hayat, M., Zamir, S. W., Khan, F. S., & Shah, M. (2021) · arXiv

Advanced Neural Network ApplicationsMultimodal Machine Learning Applications

Cited by 3,594

ECO: Efficient Convolution Operators for Tracking

Danelljan, M., Bhat, G., Khan, F. S., & Felsberg, M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 2,805

ATOM: Accurate Tracking by Overlap Maximization

Danelljan, M., Bhat, G., Khan, F. S., & Felsberg, M. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 1,591

Discriminative Scale Space Tracking

Danelljan, M., Hager, G., Khan, F. S., & Felsberg, M. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Video Surveillance and Tracking MethodsAdvanced Image and Video Retrieval Techniques

Cited by 1,315

Unveiling the Power of Deep Tracking

Bhat, G., Johnander, J., Danelljan, M., Khan, F. S., & Felsberg, M. (2018) · Lecture Notes in Computer Science

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 514

Learning the Model Update for Siamese Trackers

Zhang, L., Gonzalez-Garcia, A., Weijer, J. V. D., Danelljan, M., & Khan, F. S. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 475

Intriguing Properties of Vision Transformers

Naseer, M., Ranasinghe, K., Khan, S., Hayat, M., Khan, F. S., & Yang, M.-H. (2021) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 431

Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection

Ristea, N.-C., Madan, N., Ionescu, R. T., Nasrollahi, K., Khan, F. S., Moeslund, T. B., & Shah, M. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Anomaly Detection Techniques and ApplicationsIndustrial Vision Systems and Defect Detection

Cited by 315

Foundation Models Defining a New Era in Vision: A Survey and Outlook

Awais, M., Naseer, M., Khan, S., Anwer, R. M., Cholakkal, H., Shah, M., Yang, M.-H., & Khan, F. S. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 304

GeoChat:Grounded Large Vision-Language Model for Remote Sensing

Kuckreja, K., Danish, M. S., Naseer, M., Das, A., Khan, S., & Khan, F. S. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsRemote-Sensing Image Classification

Cited by 290

Learning Fast and Robust Target Models for Video Object Segmentation

Robinson, A., Jaremo Lawin, F., Danelljan, M., Khan, F. S., & Felsberg, M. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 158

LLM Post-Training: A Deep Dive into Reasoning Large Language Models

Kumar, K., Ashraf, T., Thawakar, O., Anwer, R. M., Cholakkal, H., Shah, M., Yang, M.-H., Torr, P. H. S., Khan, F. S., & Khan, S. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 10