A Hybrid Approach for Visual Recognition of Object States

摘要

The basic objective of my research work is to address the challenging problem of recognizing object states in a visual context by integrating data-driven and symbolic approaches. In particular, I focus on the Zero-shot variation of this task. The contributions made so far include the development of novel methods that exhibit state-of-the-art (SOTA) performance, the creation of a new object states dataset, the formulation of novel problems, the successful integration of low-level and high-level approaches, and comprehensive analyses that highlight the specific challenges posed by the problem.