70 citations · 204 across the 18 of their papers we have counts for
4 papers · 1 filter
PG-Video-LLaVA: Pixel Grounding Large Video-Language Models
Shehan Munasinghe, Rusiru Thushara, Muhammad Maaz +4
Extending image-based Large Multimodal Models (LMMs) to videos is challenging due to the inherent complexity of video data. The recent approaches extending image-based LMMs to vide…
GLaMM: Pixel Grounding Large Multimodal Model
Hanoona Rasheed, Muhammad Maaz, Sahal Shaji Mullappilly +7
Large Multimodal Models (LMMs) extend Large Language Models to the vision domain. Initial LMMs used holistic images and text prompts to generate ungrounded textual responses. Recen…
Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models
Muhammad Maaz, Hanoona Rasheed, Salman Khan +1
Conversation agents fueled by Large Language Models (LLMs) are providing a new way to interact with visual data. While there have been initial attempts for image-based conversation…
SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications
Abdelrahman Shaker, Muhammad Maaz, Hanoona Rasheed +3
Self-attention has become a defacto choice for capturing global context in various vision applications. However, its quadratic computational complexity with respect to image resolu…