DeepNav: Learning to Navigate Large Cities

We present DeepNav, a Convolutional Neural Network (CNN) based algorithm for navigating large cities using locally visible street-view images. The DeepNav agent learns to reach its destination quickly by making the correct navigation decisions at intersections. We collect a large-scale dataset of street-view images organized in a graph where nodes are connected by roads. This dataset contains 10 city graphs and more than 1 million street-view images. We propose 3 supervised learning approaches for the navigation task and show how A* search in the city graph can be used to generate supervision for the learning. Our annotation process is fully automated using publicly available mapping services and requires no human input. We evaluate the proposed DeepNav models on 4 held-out cities for navigating to 5 different types of destinations. Our algorithms outperform previous work that uses hand-crafted features and Support Vector Regression (SVR)[19].Comment: CVPR 2017 camera ready versio

Ideas and innovation in East Asia

The generation, diffusion, absorption and application of new technology, knowledge or ideas are crucial drivers of development. This paper surveys the diverse approaches to innovation adopted by East Asian economies, the problems faced and outcomes achieved, as well as possible policy lessons. Knowledge flows from advanced countries remain the primary source of new ideas in developing economies. The authors evaluate the role of three main channels for knowledge flows to East Asia - international trade, acquisition of disembodied knowledge and foreign direct investment. The paper then looks at the exceptionally fast growth in domestic innovation efforts in Korea, Taiwan (China), Singapore and China, drawing on information about R&D as well as original analysis of patent and patent citation data. Citation analysis shows that while East Asian innovations continue to draw heavily on knowledge flows from the US and Japan, citations to the same or to other East Asian economies are quickly rising, indicating the emergence of national and regional knowledge stocks as a foundation for innovation. A last section pulls together findings about policies and institutions to foster innovation, under three heads: the overall business environment for innovation (macroeconomic stability, financial development, openness, competition, intellectual property rights and the quality of communications infrastructure), human capital development, and government fiscal support for innovation.E-Business,Knowledge Economy,Economic Theory&Research,Technology Industry,Agricultural Knowledge&Information Systems

On SARS type economic effects during infectious disease outbreaks

Infectious disease outbreaks can exact a high human and economic cost through illness and death. But, as with severe acute respiratory syndrome (SARS) in East Asia in 2003, or the plague outbreak in Surat, India, in 1994, they can also create severe economic disruptions even when there is, ultimately, relatively little illness or death. Such disruptions are commonly the result of uncoordinated and panicky efforts by individuals to avoid becoming infected, of preventive activity. This paper places these"SARS type"effects in the context of research on economic epidemiology, in which behavioral responses to disease risk have both economic and epidemiological consequences. The paper looks in particular at how people form subjective probability judgments about disease risk. Public opinion surveys during the SARS outbreak provide suggestive evidence that people did indeed at times hold excessively high perceptions of the risk of becoming infected, or, if infected, of dying from the disease. The paper discusses research in behavioral economics and the theory of information cascades that may shed light on the origin of such biases. The authors consider whether public information strategies can help reduce unwarranted panic. A preliminary question is why governments often seem to have strong incentives to conceal information about infectious disease outbreaks. The paper reviews recent game-theoretic analysis that clarifies government incentives. An important finding is that government incentives to conceal decline the more numerous are non-official sources of information about a possible disease outbreak. The findings suggest that honesty may indeed be the best public policy under modern conditions of easy mass global communications.Health Monitoring&Evaluation,Disease Control&Prevention,Population Policies,Hazard Risk Management,Gender and Health

Human Rights and Development Practice

In the past two decades, there has been a growing engagement between development and human rights practitioners and thinkers. But are participants in this dialogue still mainly talking past each other? Or has there been valuable cross-fertilization and learning—the Millennium Development Goals (MDGs) themselves being a fruit of this convergence? This note addresses three points. The first point is the growing convergence between human rights and development thinking along several dimensions, particularly on social and economic rights. The second point is a consideration of the continuing areas of difference or divergence and of outstanding or open questions. Are these areas of conflict or are they valuable complementarities? The third point asks where are we with MDGs on the ground, and what can the dialogue between human rights and development contribute to furthering progress on MDGs?Human rights, MDGs, Millennium Development Goals, social rights, economic rights, development, developing countires, poverty reduction, World Bank

Occlusion-Aware Object Localization, Segmentation and Pose Estimation

We present a learning approach for localization and segmentation of objects in an image in a manner that is robust to partial occlusion. Our algorithm produces a bounding box around the full extent of the object and labels pixels in the interior that belong to the object. Like existing segmentation aware detection approaches, we learn an appearance model of the object and consider regions that do not fit this model as potential occlusions. However, in addition to the established use of pairwise potentials for encouraging local consistency, we use higher order potentials which capture information at the level of im- age segments. We also propose an efficient loss function that targets both localization and segmentation performance. Our algorithm achieves 13.52% segmentation error and 0.81 area under the false-positive per image vs. recall curve on average over the challenging CMU Kitchen Occlusion Dataset. This is a 42.44% decrease in segmentation error and a 16.13% increase in localization performance compared to the state-of-the-art. Finally, we show that the visibility labelling produced by our algorithm can make full 3D pose estimation from a single image robust to occlusion.Comment: British Machine Vision Conference 2015 (poster

Dealing with Dutch Disease

This note looks at so-called Dutch disease, a phenomenon reflecting changes in the structure of production in the wake of a favorable shock (such as a large natural resource discovery, a rise in the international price of an exportable commodity, or the presence of sustained aid or capital inflows). Where the natural resources discovered are oil or minerals, a contraction or stagnation of manufacturing and agriculture could accompany the positive effects of the shock, according to the theory. The note considers channels through which such natural resource wealth can affect the economy. It also focuses on the development implications of Dutch disease, particularly the potential negative effects related to productivity dynamics and volatility; and concludes with a summary of possible policy responses, including the mix of fiscal, exchange rate, and structural reform policies.Dutch disease, shock, natural resources, comodities, capital, aid, oil, minerals, manufacturing, agriculture, wealth, volatility