HRFuser: A Multi-resolution Sensor Fusion Architecture for 2D Object Detection

Besides standard cameras, autonomous vehicles typically include multipleadditional sensors, such as lidars and radars, which help acquire richerinformation for perceiving the content of the driving scene. While severalrecent works focus on fusing certain pairs of sensors - such as camera andlidar or camera and radar - by using architectural components specific to theexamined setting, a generic and modular sensor fusion architecture is missingfrom the literature. In this work, we focus on 2D object detection, afundamental high-level task which is defined on the 2D image domain, andpropose HRFuser, a multi-resolution sensor fusion architecture that scalesstraightforwardly to an arbitrary number of input modalities. The design ofHRFuser is based on state-of-the-art high-resolution networks for image-onlydense prediction and incorporates a novel multi-window cross-attention block asthe means to perform fusion of multiple modalities at multiple resolutions.Even though cameras alone provide very informative features for 2D detection,we demonstrate via extensive experiments on the nuScenes and Seeing Through Fogdatasets that our model effectively leverages complementary features fromadditional modalities, substantially improving upon camera-only performance andconsistently outperforming state-of-the-art fusion methods for 2D detectionboth in normal and adverse conditions. The source code will be made publiclyavailable.<br

Bleeding Hearts, Profiteers, or Both: Specialist Physician Fees in an Unregulated Market

Copyright © 2016 John Wiley & Sons, Ltd. This study shows that, in an unregulated fee-setting environment, specialist physicians practise price discrimination on the basis of their patients' income status. Our results are consistent with profit maximisation behaviour by specialists. These findings are based on a large population survey that is linked to administrative medical claims records. We find that, for an initial consultation, specialist physicians charge their high-income patients AU$26 more than their low-income patients. While this gap equates to a 19% lower fees for the poorest patients (bottom 25% of the household income distribution), it is unlikely to remove the substantial financial barriers they face in accessing specialist care. There are large variations across specialties, with neurologists exhibiting the largest fee gap between the high-income and low-income patients. Several possible channels for deducing the patient's income are examined. We find that patient characteristics such as age, health concession card status and private health insurance status are all used by specialists as proxies for income status. These characteristics are particularly important to further practise price discrimination among the low-income patients but are less relevant for the high-income patients. Copyright © 2016 John Wiley & Sons, Ltd

Talenquests in de praktijk: een queeste

Wetensch. publicatieFaculteit der Lettere

3D modeling and registration under wide baseline conditions

During the 90s important progess has been made in the area of structure-from-motion. From a series of closely spaced images a 3D model of the observed scene can now be reconstructed, without knowledge about the subsequent camera positions or settings. From nothing but a video, the camera trajectory and scene shape are extracted. Progress has also been important in the area of structured light techniques. Rather than having to use slow and/or bulky laser scanners, compact one-shot systems have been developed. Upon projection of a pattern onto the scene, its 3D shape and texture can be extracted from a single image. This paper presents recent extensions on both strands, that have a common theme: how to cope with large baseline conditions. In the case of shape-from-video we discuss ways to find correspondences and, hence, extract 3D shapes even when the images are taken far apart. In the case of structured light, the problem solved is how to combine partial 3D patches into complete models, without a good initialisation of their relative poses.