Vision Model
Vision models are artificial intelligence systems designed to interpret and understand visual information, aiming to replicate aspects of human visual perception and reasoning. Current research emphasizes improving efficiency and generalization across diverse tasks, focusing on architectures like Vision Transformers and Convolutional Neural Networks, often incorporating large language models for multimodal understanding and instruction following. This field is crucial for advancing various applications, from medical image analysis and robotic manipulation to enhancing accessibility and creative tools, with ongoing efforts to improve model robustness, explainability, and alignment with human perception.
Papers
Few-Shot Image Classification and Segmentation as Visual Question Answering Using Vision-Language Models
Tian Meng, Yang Tao, Ruilin Lyu, Wuliang Yin
Quantization Effects on Neural Networks Perception: How would quantization change the perceptual field of vision models?
Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani, Alessandro Bruno