8 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…
Panoptic Segmentation Forecasting
Colin Graber, Grace Tsai, Michael Firman +2
Our goal is to forecast the near future given a set of recent observations. We think this ability to forecast, i.e., to anticipate, is integral for the success of autonomous agents…
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,…
DiverseNet: When One Right Answer is not Enough
Michael Firman, Neill D. F. Campbell, Lourdes Agapito +1
Many structured prediction tasks in machine vision have a collection of acceptable answers, instead of one definitive ground truth answer. Segmentation of images, for example, is s…
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…