Object State

Object state recognition focuses on identifying the condition or status of objects in images and videos, a crucial step for enabling machines to understand and interact with the physical world. Current research emphasizes improving the accuracy of object state classification using vision-language models (VLMs) and large language models (LLMs), often incorporating techniques like self-supervised learning and multi-task learning to address data scarcity and ambiguity. These advancements are driving progress in robotics, particularly for tasks involving manipulation and task planning, and are also improving the capabilities of video understanding systems. The development of new benchmark datasets and the exploration of novel architectures, such as vision transformers, are key to further progress in this field.