14 citations · 30 across the 12 of their papers we have counts for
14 papers
RoboTALES: Learning Reasoning-Guided Robot Policies via Task-Aligned Simulated Futures
Hanan Gani, Tejal Kulkarni, Madhoolika Chodavarapu +2
Pretrained video generative models are promising backbones for visuomotor control, but their imagined futures often drift from task intent and are not reliably action-conditional.…
Recovering Cloud Microstructures with Cascaded Diffusion Inversion
Hanan Gani, Guy Pulik, Daniel Rosenfeld +2
High-resolution satellite imagery is critical for observing fine-scale cloud structures that inform weather modification strategies like cloud seeding for rain-enhancement. However…
VideoMolmo: Spatio-Temporal Grounding Meets Pointing
Ghazi Shazan Ahmad, Ahmed Heakl, Hanan Gani +4
Spatio-temporal localization is vital for precise interactions across diverse domains, from biological research to autonomous navigation and interactive interfaces. Current video-b…
Aurelia: Test-time Reasoning Distillation in Audio-Visual LLMs
Sanjoy Chowdhury, Hanan Gani, Nishit Anand +5
Recent advancements in reasoning optimization have greatly enhanced the performance of large language models (LLMs). However, existing work fails to address the complexities of aud…
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…
Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization
Jameel Hassan, Hanan Gani, Noor Hussein +4
The promising zero-shot generalization of vision-language models such as CLIP has led to their adoption using prompt learning for numerous downstream tasks. Previous works have sho…
LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts
Hanan Gani, Shariq Farooq Bhat, Muzammal Naseer +2
Diffusion-based generative models have significantly advanced text-to-image generation but encounter challenges when processing lengthy and intricate text prompts describing comple…
How to Train Vision Transformer on Small-scale Datasets?
Hanan Gani, Muzammal Naseer, Mohammad Yaqub
Vision Transformer (ViT), a radically different architecture than convolutional neural networks offers multiple advantages including design simplicity, robustness and state-of-the-…
A Supervised Learning Methodology for Real-Time Disguised Face Recognition in the Wild
Saumya Kumaar, Abhinandan Dogra, Abrar Majeedi +3
Facial recognition has always been a challeng- ing task for computer vision scientists and experts. Despite complexities arising due to variations in camera parameters, illuminatio…