  The intelligent dialogue system, aiming at communicating with humans
harmoniously with natural language, is brilliant for promoting the advancement
of human-machine interaction in the era of artificial intelligence. With the
gradually complex human-computer interaction requirements (e.g., multimodal
inputs, time sensitivity), it is difficult for traditional text-based dialogue
system to meet the demands for more vivid and convenient interaction.
Consequently, Visual Context Augmented Dialogue System (VAD), which has the
potential to communicate with humans by perceiving and understanding multimodal
information (i.e., visual context in images or videos, textual dialogue
history), has become a predominant research paradigm. Benefiting from the
consistency and complementarity between visual and textual context, VAD
possesses the potential to generate engaging and context-aware responses. For
depicting the development of VAD, we first characterize the concepts and unique
features of VAD, and then present its generic system architecture to illustrate
the system workflow. Subsequently, several research challenges and
representative works are detailed investigated, followed by the summary of
authoritative benchmarks. We conclude this paper by putting forward some open
issues and promising research trends for VAD, e.g., the cognitive mechanisms of
human-machine dialogue under cross-modal dialogue context, and
knowledge-enhanced cross-modal semantic interaction.
