papers

Publications (12)

cs.CV2023

Virtual Occlusions Through Implicit Depth

Jamie Watson, Mohamed Sayed, Zawar Qureshi +4

For augmented reality (AR), it is important that virtual assets appear to `sit among' real world objects. The virtual element should variously occlude and be occluded by real matte…

cs.CV2021

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…

cs.CV2022

SimpleRecon: 3D Reconstruction Without 3D Convolutions

Mohamed Sayed, John Gibson, Jamie Watson +3

Traditionally, 3D indoor scene reconstruction from posed images happens in two phases: per-image depth estimation, followed by depth merging and surface reconstruction. Recently, a…

cs.CV2021

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,…

cs.CV2025

PlaceIt3D: Language-Guided Object Placement in Real 3D Scenes

Ahmed Abdelreheem, Filippo Aleotti, Jamie Watson +6

We introduce the novel task of Language-Guided Object Placement in Real 3D Scenes. Our model is given a 3D scene's point cloud, a 3D asset, and a textual prompt broadly describing…

cs.CV2020

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…