14 citations · 30 across the 12 of their papers we have counts for
6 papers · 1 filter
VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos
Shehan Munasinghe, Hanan Gani, Wenqi Zhu +4
Fine-grained alignment between videos and text is challenging due to complex spatial and temporal dynamics in videos. Existing video-based Large Multimodal Models (LMMs) handle bas…
AgriCLIP: Adapting CLIP for Agriculture and Livestock via Domain-Specialized Cross-Model Alignment
Umair Nawaz, Muhammad Awais, Hanan Gani +4
Capitalizing on vast amount of image-text data, large-scale vision-language pre-training has demonstrated remarkable zero-shot capabilities and has been utilized in several applica…
Test-Time Low Rank Adaptation via Confidence Maximization for Zero-Shot Generalization of Vision-Language Models
Raza Imam, Hanan Gani, Muhammad Huzaifa +1
The conventional modus operandi for adapting pre-trained vision-language models (VLMs) during test-time involves tuning learnable prompts, ie, test-time prompt tuning. This paper i…
VANE-Bench: Video Anomaly Evaluation Benchmark for Conversational LMMs
Rohit Bharadwaj, Hanan Gani, Muzammal Naseer +2
The recent developments in Large Multi-modal Video Models (Video-LMMs) have significantly enhanced our ability to interpret and analyze video data. Despite their impressive capabil…
MedContext: Learning Contextual Cues for Efficient Volumetric Medical Segmentation
Hanan Gani, Muzammal Naseer, Fahad Khan +1
Volumetric medical segmentation is a critical component of 3D medical image analysis that delineates different semantic regions. Deep neural networks have significantly improved vo…
Multi-Attribute Vision Transformers are Efficient and Robust Learners
Hanan Gani, Nada Saadi, Noor Hussein +1
Since their inception, Vision Transformers (ViTs) have emerged as a compelling alternative to Convolutional Neural Networks (CNNs) across a wide spectrum of tasks. ViTs exhibit not…