13 citations · 17 across the 18 of their papers we have counts for
7 papers · 1 filter
RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone
Mustafa Munir, Md Mostafijur Rahman, Radu Marculescu
Vision transformers (ViTs) have dominated computer vision in recent years. However, ViTs are computationally expensive and not well suited for mobile devices; this led to the preva…
CrediRAG: Network-Augmented Credibility-Based Retrieval for Misinformation Detection in Reddit
Ashwin Ram, Yigit Ege Bayiz, Arash Amini +2
Fake news threatens democracy and exacerbates the polarization and divisions in society; therefore, accurately detecting online misinformation is the foundation of addressing this…
Scaling Graph Convolutions for Mobile Vision
William Avery, Mustafa Munir, Radu Marculescu
To compete with existing mobile architectures, MobileViG introduces Sparse Vision Graph Attention (SVGA), a fast token-mixing operator based on the principles of GNNs. However, Mob…
Ada-VE: Training-Free Consistent Video Editing Using Adaptive Motion Prior
Tanvir Mahmud, Mustafa Munir, Radu Marculescu +1
Video-to-video synthesis poses significant challenges in maintaining character consistency, smooth temporal transitions, and preserving visual quality during fast motion. While rec…
PP-SAM: Perturbed Prompts for Robust Adaptation of Segment Anything Model for Polyp Segmentation
Md Mostafijur Rahman, Mustafa Munir, Debesh Jha +2
The Segment Anything Model (SAM), originally designed for general-purpose segmentation tasks, has been used recently for polyp segmentation. Nonetheless, fine-tuning SAM with data…
EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation
Md Mostafijur Rahman, Mustafa Munir, Radu Marculescu
An efficient and effective decoding mechanism is crucial in medical image segmentation, especially in scenarios with limited computational resources. However, these decoding mechan…
GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs
Mustafa Munir, William Avery, Md Mostafijur Rahman +1
Vision graph neural networks (ViG) offer a new avenue for exploration in computer vision. A major bottleneck in ViGs is the inefficient k-nearest neighbor (KNN) operation used for…