In the past few years, advances in machine learning have fueled an explosive growth of
descriptive and generative models of animal behavior. These new approaches offer higher …

Animals move in three dimensions (3D). Thus, 3D measurement is necessary to report the
true kinematics of animal movement. Existing 3D measurement techniques draw on …

The study of naturalistic social behavior requires quantification of animals' interactions. This
is generally done through manual annotation—a highly time-consuming and tedious …

The quantification of animal social behaviour is an essential step to reveal brain functions
and psychiatric disorders during interaction phases. While deep learning-based approaches …

Abstract We present the Caltech Fish Counting Dataset (CFC), a large-scale dataset for
detecting, tracking, and counting fish in sonar videos. We identify sonar videos as a rich …

We introduce VideoPrism, a general-purpose video encoder that tackles diverse video
understanding tasks with a single frozen model. We pretrain VideoPrism on a …

We propose a method for learning the posture and structure of agents from unlabelled
behavioral videos. Starting from the observation that behaving agents are generally the …

Robots navigating in crowded areas should negotiate free space with humans rather than
fully controlling collision avoidance, as this can lead to freezing behavior. Game theory …

Quantifying motion in 3D is important for studying the behavior of humans and other
animals, but manual pose annotations are expensive and time-consuming to obtain. Self …

The study of complex behaviors is often challenging when using manual annotation due to
the absence of quantifiable behavioral definitions and the subjective nature of behavioral …