Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking

Understand

The ability to detect and track objects in the visual world is a crucial skill for any intelligent agent, as it is a necessary precursor to any object-level reasoning process.

• Moreover, it is important that agents learn to track objects without supervision (i.e.
• without access to annotated training videos) since this will allow agents to begin operating in new environments with minimal human assistance.
• The task of learning to discover and track objects in videos, which we call \textit{unsupervised object tracking}, has grown in prominence in recent years; however, most architectures that address it still struggle to deal with large scenes containing many objects.