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Multi-View Stereo via Volumetric Graph-Cuts
This paper presents a novel formulation for the multi-view scene reconstruction problem. While this formulation benefits from a volumetric scene representation, it is amenable to a computationally tractable global optimisation using Graph-cuts. The algorithm proposed uses the visual hull of…
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Deep Reinforcement Learning for Autonomous Traffic Light Control
In urban areas, the efficiency of traffic flows largely depends on signal operation and expansion of the existing signal infrastructure is not feasible due to spatial, economic and environmental constraints. In this paper, we address the problem of congestion around…
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Bayesian Stochastic Mesh Optimization for 3D reconstruction
We describe a mesh based approach to the problem of structure from motion. The input to the algorithm is a small set of images, sparse noisy feature correspondences (such as those provided by a Harris corner detector and cross correlation)…
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Shadows in Three-Source Photometric Stereo
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A Generative Model for Online Depth Fusion
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Reconstruction in the Round Using Photometric Normals and Silhouettes.
This paper addresses the problem of obtaining complete, detailed reconstructions of shiny textureless objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under varying illumination conditions. In contrast with previous photometric stereo techniques,…
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Automatic Object Segmentation from Calibrated Images
This paper addresses the problem of automatically obtaining the object/background segmentation of a rigid 3D object observed in a set of images that have been calibrated for camera pose and intrinsics. Such segmentations can be used to obtain a shape…
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Traffic3D: A Rich 3D-Traffic Environment to Train Intelligent Agents
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Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps
Self-supervised monocular depth estimation has been a subject of intense study in recent years, because of its applications in robotics and autonomous driving. Much of the recent work focuses on improving depth estimation by increasing architecture complexity. This paper shows…
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A deep learning pipeline for semantic facade segmentation
We propose an algorithm that provides a pixel-wise classification of building facades. Building facades provide a rich environment for testing semantic segmentation techniques. They come in a variety of styles that reflect both appearance and layout characteristics. On the other…
