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Learning Invariant World State Representations with Predictive Coding
Herein, we propose a framework for evaluating visual representations for illumination invariance in the context of depth perception.
A Study on Multimodal and Interactive Explanations for Visual Question Answering
Explainability and interpretability of AI models is an essential factor affecting the safety of AI.
Generating Natural Language Explanations for Visual Question Answering using Scene Graphs and Visual Attention
In this paper, we present a novel approach for the task of eXplainable Question Answering (XQA), i. e., generating natural language (NL) explanations for the Visual Question Answering (VQA) problem.
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