1 code implementation • 27 Feb 2024 • Hanan Gani, Muzammal Naseer, Fahad Khan, Salman Khan
The proposed approach induces contextual knowledge in the network by learning to reconstruct the missing organ or parts of an organ in the output segmentation space.
1 code implementation • 12 Feb 2024 • Hanan Gani, Nada Saadi, Noor Hussein, Karthik Nandakumar
Since their inception, Vision Transformers (ViTs) have emerged as a compelling alternative to Convolutional Neural Networks (CNNs) across a wide spectrum of tasks.
no code implementations • NeurIPS 2023 • Jameel Hassan, Hanan Gani, Noor Hussein, Muhammad Uzair Khattak, Muzammal Naseer, Fahad Shahbaz Khan, Salman Khan
The promising zero-shot generalization of vision-language models such as CLIP has led to their adoption using prompt learning for numerous downstream tasks.
1 code implementation • 16 Oct 2023 • Hanan Gani, Shariq Farooq Bhat, Muzammal Naseer, Salman Khan, Peter Wonka
Diffusion-based generative models have significantly advanced text-to-image generation but encounter challenges when processing lengthy and intricate text prompts describing complex scenes with multiple objects.
2 code implementations • 13 Oct 2022 • Hanan Gani, Muzammal Naseer, Mohammad Yaqub
However, in contrast to convolutional neural networks, Vision Transformer lacks inherent inductive biases.
1 code implementation • 8 Sep 2018 • Saumya Kumaar, Abhinandan Dogra, Abrar Majeedi, Hanan Gani, Ravi M. Vishwanath, S. N. Omkar
The modern day scenario, where security is of prime concern, regular face identification techniques do not perform as required when the faces are disguised, which calls for a different approach to handle situations where intruders have their faces masked.