This work surveys recent work in the very nascent field of probabilistic detection and pesents insights and promising avenues for future research in this area.
This work introduces and formalises the problem of recognising intersections from drastically different viewpoints to enable place recognition for SLAM using a siamese convolutional recurrent architecture trained to classify pairs of short video streams.
CTCNet proposed using the compositional property of transformations to self-supervise learning of visual odometry from images.