Shah, Mubarak

Ucf101: A dataset of 101 human actions classes from videos in the wild

Soomro, K., Zamir, A. R., & Shah, M. (2012) · arXiv

Human Pose and Action RecognitionHand Gesture Recognition Systems

Cited by 4,575

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

Shape-from-shading: A survey

Zhang, R., Tsai, P.-S., Cryer, J. E., & Shah, M. (1999) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Vision and ImagingComputer Graphics and Visualization Techniques

Cited by 1,731

A Fast algorithm for active contours and curvature estimation

Williams, D. J., & Shah, M. (1992) · CVGIP: Image Understanding

Medical Image Segmentation TechniquesImage and Object Detection Techniques

Cited by 1,101

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

Self-supervised learning for videos: A survey

Schiappa, M. C., Rawat, Y. S., & Shah, M. (2023) · ACM Computing Surveys

Domain Adaptation and Few-Shot LearningHuman Pose and Action Recognition

Cited by 155

Content based video matching using spatiotemporal volumes

Basharat, A., Zhai, Y., & Shah, M. (2008) · Computer Vision and Image Understanding

Video Analysis and SummarizationAdvanced Image and Video Retrieval Techniques

Cited by 94