  In psychoanalysis, generating interpretations to one's psychological state
through visual creations is facing significant demands. The two main tasks of
existing studies in the field of computer vision, sentiment/emotion
classification and affective captioning, can hardly satisfy the requirement of
psychological interpreting. To meet the demands for psychoanalysis, we
introduce a challenging task, \textbf{V}isual \textbf{E}motion
\textbf{I}nterpretation \textbf{T}ask (VEIT). VEIT requires AI to generate
reasonable interpretations of creator's psychological state through visual
creations. To support the task, we present a multimodal dataset termed SpyIn
(\textbf{S}and\textbf{p}la\textbf{y} \textbf{In}terpretation Dataset), which is
psychological theory supported and professional annotated. Dataset analysis
illustrates that SpyIn is not only able to support VEIT, but also more
challenging compared with other captioning datasets. Building on SpyIn, we
conduct experiments of several image captioning method, and propose a
visual-semantic combined model which obtains a SOTA result on SpyIn. The
results indicate that VEIT is a more challenging task requiring scene graph
information and psychological knowledge. Our work also show a promise for AI to
analyze and explain inner world of humanity through visual creations.
