Vision Paper

Vision research currently focuses on developing robust and efficient methods for processing and understanding visual information, often integrating it with other modalities like language and touch. Key areas include improving the accuracy and efficiency of models like transformers and exploring alternatives such as Mamba and structured state space models for various tasks, ranging from object detection and segmentation to navigation and scene understanding. This work is driven by the need for improved performance in applications such as robotics, autonomous systems, medical image analysis, and assistive technologies, with a strong emphasis on addressing challenges like limited data, computational cost, and generalization to unseen scenarios.