Kitchen Environment

Research on kitchen environments is increasingly focused on using computer vision and natural language processing to understand and model activities within kitchens. Current efforts involve developing large datasets of kitchen videos and images, coupled with the application of deep learning models like transformers and novel algorithms for tasks such as 6D object pose estimation, fine-grained hand action recognition, and liquid manipulation control. This work aims to improve robotic capabilities in kitchens, enhance food-related applications (e.g., recipe generation, dietary recommendations), and advance our understanding of human-environment interaction through the analysis of complex visual and textual data.