5 papers · 1 filter
Single Image Depth Prediction with Wavelet Decomposition
Michaël Ramamonjisoa, Michael Firman, Jamie Watson +2
We present a novel method for predicting accurate depths from monocular images with high efficiency. This optimal efficiency is achieved by exploiting wavelet decomposition, which…
The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth
Jamie Watson, Oisin Mac Aodha, Victor Prisacariu +2
Self-supervised monocular depth estimation networks are trained to predict scene depth using nearby frames as a supervision signal during training. However, for many applications,…
Learning Stereo from Single Images
Jamie Watson, Oisin Mac Aodha, Daniyar Turmukhambetov +2
Supervised deep networks are among the best methods for finding correspondences in stereo image pairs. Like all supervised approaches, these networks require ground truth data duri…
Footprints and Free Space from a Single Color Image
Jamie Watson, Michael Firman, Aron Monszpart +1
Understanding the shape of a scene from a single color image is a formidable computer vision task. However, most methods aim to predict the geometry of surfaces that are visible to…
Self-Supervised Monocular Depth Hints
Jamie Watson, Michael Firman, Gabriel J. Brostow +1
Monocular depth estimators can be trained with various forms of self-supervision from binocular-stereo data to circumvent the need for high-quality laser scans or other ground-trut…