activity
20222024
most citedFoundational Models Defining a New Era in Vision: A Survey and Outlook

68 citations · 111 across the 24 of their papers we have counts for

collaborators

24 papers

cs.CV2024

Efficient 3D-Aware Facial Image Editing via Attribute-Specific Prompt Learning

Amandeep Kumar, Muhammad Awais, Sanath Narayan +3

Drawing upon StyleGAN's expressivity and disentangled latent space, existing 2D approaches employ textual prompting to edit facial images with different attributes. In contrast, 3D…

eess.IV2024

Medical Image Segmentation Using Directional Window Attention

Daniya Najiha Abdul Kareem, Mustansar Fiaz, Noa Novershtern +1

Accurate segmentation of medical images is crucial for diagnostic purposes, including cell segmentation, tumor identification, and organ localization. Traditional convolutional neu…

cs.CV2024

ChangeBind: A Hybrid Change Encoder for Remote Sensing Change Detection

Mubashir Noman, Mustansar Fiaz, Hisham Cholakkal

Change detection (CD) is a fundamental task in remote sensing (RS) which aims to detect the semantic changes between the same geographical regions at different time stamps. Existin…

cs.CV20241 cited

PARIS3D: Reasoning-based 3D Part Segmentation Using Large Multimodal Model

Amrin Kareem, Jean Lahoud, Hisham Cholakkal

Recent advancements in 3D perception systems have significantly improved their ability to perform visual recognition tasks such as segmentation. However, these systems still heavil…

cs.CV2024

ELGC-Net: Efficient Local-Global Context Aggregation for Remote Sensing Change Detection

Mubashir Noman, Mustansar Fiaz, Hisham Cholakkal +2

Deep learning has shown remarkable success in remote sensing change detection (CD), aiming to identify semantic change regions between co-registered satellite image pairs acquired…

cs.CV20242 cited

Rethinking Transformers Pre-training for Multi-Spectral Satellite Imagery

Mubashir Noman, Muzammal Naseer, Hisham Cholakkal +3

Recent advances in unsupervised learning have demonstrated the ability of large vision models to achieve promising results on downstream tasks by pre-training on large amount of un…