  We present an instance segmentation algorithm trained and applied to a CCTV
recording of beef cattle during a winter finishing period. A fully
convolutional network was transformed into an instance segmentation network
that learns to label each instance of an animal separately. We introduce a
conceptually simple framework that the network uses to output a single
prediction for every animal. These results are a contribution towards behaviour
analysis in winter finishing beef cattle for early detection of animal
welfare-related problems.
