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Vision-language models (VLMs), capable of processing both images and text, have gained immense popularity due to their versatility in solving a wide range of tasks, from…
In recent years, computer vision has made significant strides by leveraging advanced neural network architectures to tackle complex tasks such as image classification, object detection, and…
Video understanding is one of the evolving areas of research in artificial intelligence (AI), focusing on enabling machines to comprehend and analyze visual content. Tasks like…
Knowledge Distillation has gained popularity for transferring the expertise of a “teacher” model to a smaller “student” model. Initially, an iterative learning process involving a high-capacity…
The advent of large language models (LLMs) like GPT-4 has sparked excitement around enhancing them with multimodal capabilities to understand visual data alongside text. However, previous…
Vision Transformers (ViT) and Convolutional Neural Networks (CNN) have emerged as key players in image processing in the competitive landscape of machine learning technologies. Their development…
Understanding and mitigating hallucinations in vision-language models (VLVMs) is an emerging field of research that addresses the generation of coherent but factually incorrect responses by these…
Adopting finetuned adapters has become a cornerstone in generative image models, facilitating customized image creation while minimizing storage requirements. This transition has catalyzed the development of…
The introduction of Audio Description (AD) marks a big step towards making video content more accessible. AD provides a spoken narrative of important visual elements within…
Graph Neural Network (GNN)–based motion planning has emerged as a promising approach in robotic systems for its efficiency in pathfinding and navigation tasks. This approach leverages…