A Scene Understanding Challenge Problem was released by AFRL at this conference in 2015 in response to DARPA’s Mathematics, Sensing, Exploitation, and Execution (MSEE) program. We consider a scene understanding system as a generalization of typical sensor exploitation systems where instead of performing a narrowly deﬁned task (e.g., detect, track, classify, etc.), the system can perform general user-deﬁned tasks speciﬁed in a query language. That paper1 laid out the general challenges and methods for developing scene understanding performance models. This is an enormously challenging problem, so now AFRL is illustrating the methods with a baseline system primarily developed by the University of California, Los Angeles (UCLA) during the MSEE program. This system will be publicly available for others to utilize, compare, and contrast with related methods. This paper will further explain and provide insights into the challenges, illustrating them with examples from a publicly available data set. Our intent is that these tools will relieve the requirement for developing an entire system and enable progress to occur by focusing on individual elements of the system. Finally, we will provide details as to how interested researchers may obtain the system and the data.