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pro vyhledávání: '"Saif, Ullah"'
Inspired by the natural motion of insects, fish, and other animals, flapping airfoils have gained significant importance due to their applications in fields such as ship propulsion, micro aerial vehicles, and autonomous underwater vehicles. Over the
Externí odkaz:
http://arxiv.org/abs/2410.23909
Autor:
Sarode, Shalini, Khan, Muhammad Saif Ullah, Shehzadi, Tahira, Stricker, Didier, Afzal, Muhammad Zeshan
We propose ClassroomKD, a novel multi-mentor knowledge distillation framework inspired by classroom environments to enhance knowledge transfer between student and multiple mentors. Unlike traditional methods that rely on fixed mentor-student relation
Externí odkaz:
http://arxiv.org/abs/2409.20237
Autor:
Khan, Muhammad Saif Ullah, Khan, Muhammad Ahmed Ullah, Afzal, Muhammad Zeshan, Stricker, Didier
This paper reformulates cross-dataset human pose estimation as a continual learning task, aiming to integrate new keypoints and pose variations into existing models without losing accuracy on previously learned datasets. We benchmark this formulation
Externí odkaz:
http://arxiv.org/abs/2409.20469
In this paper, we examine the coupling between odor dynamics and vortex dynamics around undulating bodies, with a focus on bio-inspired propulsion mechanisms. Utilizing computational fluid dynamics (CFD) simulations with an in-house Immersed-Boundary
Externí odkaz:
http://arxiv.org/abs/2408.16136
Reconstructing texture-less surfaces poses unique challenges in computer vision, primarily due to the lack of specialized datasets that cater to the nuanced needs of depth and normals estimation in the absence of textural information. We introduce "S
Externí odkaz:
http://arxiv.org/abs/2406.15831
Autor:
Khan, Muhammad Saif Ullah, Shehzadi, Tahira, Noor, Rabeya, Stricker, Didier, Afzal, Muhammad Zeshan
Automated signature verification on bank checks is critical for fraud prevention and ensuring transaction authenticity. This task is challenging due to the coexistence of signatures with other textual and graphical elements on real-world documents. V
Externí odkaz:
http://arxiv.org/abs/2406.14370
The Situational Instructions Database (SID) addresses the need for enhanced situational awareness in artificial intelligence (AI) systems operating in dynamic environments. By integrating detailed scene graphs with dynamically generated, task-specifi
Externí odkaz:
http://arxiv.org/abs/2406.13302
Human pose estimation is a key task in computer vision with various applications such as activity recognition and interactive systems. However, the lack of consistency in the annotated skeletons across different datasets poses challenges in developin
Externí odkaz:
http://arxiv.org/abs/2405.20084
Autor:
Sinha, Sankalp, Khan, Muhammad Saif Ullah, Sheikh, Talha Uddin, Stricker, Didier, Afzal, Muhammad Zeshan
Zero-shot learning has been extensively investigated in the broader field of visual recognition, attracting significant interest recently. However, the current work on zero-shot learning in document image classification remains scarce. The existing s
Externí odkaz:
http://arxiv.org/abs/2405.03660
Autor:
Khan, Muhammad Saif Ullah, Naeem, Muhammad Ferjad, Tombari, Federico, Van Gool, Luc, Stricker, Didier, Afzal, Muhammad Zeshan
We present a novel LLM-based pipeline for creating contextual descriptions of human body poses in images using only auxiliary attributes. This approach facilitates the creation of the MPII Pose Descriptions dataset, which includes natural language an
Externí odkaz:
http://arxiv.org/abs/2403.06904