Visual Grounding

Visual grounding is the task of connecting natural language descriptions to corresponding regions within an image or 3D scene. Current research focuses on improving the accuracy and efficiency of visual grounding models, often employing transformer-based architectures and leveraging large multimodal language models (MLLMs) for enhanced feature fusion and reasoning capabilities. This field is crucial for advancing embodied AI, enabling robots and other agents to understand and interact with the world through natural language, and has significant implications for applications such as robotic manipulation, visual question answering, and medical image analysis.