21,765 research outputs found
Bridging Implicit and Explicit Geometric Transformation for Single-Image View Synthesis
No full textCreating novel views from a single image has achieved tremendous strides with advanced autoregressive models, as unseen regions have to be inferred from the visible scene contents. Although recent methods generate high-quality novel views, synthesizing with only one explicit or implicit 3D geometry has a trade-off between two objectives that we call the "seesaw" problem: 1) preserving reprojected contents and 2) completing realistic out-of-view regions. Also, autoregressive models require a considerable computational cost. In this paper, we propose a single-image view synthesis framework for mitigating the seesaw problem while utilizing an efficient non-autoregressive model. Motivated by the characteristics that explicit methods well preserve reprojected pixels and implicit methods complete realistic out-of-view regions, we introduce a loss function to complement two renderers. Our loss function promotes that explicit features improve the reprojected area of implicit features and implicit features improve the out-of-view area of explicit features. With the proposed architecture and loss function, we can alleviate the seesaw problem, outperforming autoregressive-based state-of-the-art methods and generating an image approximate to 100 times faster. We validate the efficiency and effectiveness of our method with experiments on RealEstate10 K and ACID datasets.
Rethinking Training Schedules For Verifiably Robust Networks
No full textNew and stronger adversarial attacks can threaten existing defenses. This possibility highlights the importance of certified defense methods that train deep neural networks with verifiably robust guarantees. A range of certified defense methods has been proposed to train neural networks with verifiably robustness guarantees, among which Interval Bound Propagation (IBP) and CROWN-IBP have been demonstrated to be the most effective. However, we observe that CROWN-IBP and IBP are suffering from Low Epsilon Overfitting (LEO), a problem arising from their training schedule that increases the input perturbation bound. We show that LEO can yield poor results even for a simple linear classifier. We also investigate the evidence of LEO from experiments under conditions of worsening LEO. Based on these observations, we propose a new training strategy, BatchMix, which mixes various input perturbation bounds in a mini-batch to alleviate the LEO problem. Experimental results on MNIST and CIFAR10 datasets show that BatchMix can make the performance of IBP and CROWN-IBP better by mitigating LEO
Fine-Grained Multi-Class Object Counting
No full textMany animal species in the wild are at the risk of extinction. To deal with this situation, ecologists have monitored the population changes of endangered species. However, the current wildlife monitoring method is extremely laborious as the animals are counted manually. Automated counting of animals by species can facilitate this work and further renew the ways for ecological studies. However, to the best of our knowledge, few works and publicly available datasets have been proposed on multi-class object counting which is applicable to counting several animal species. In this paper, we propose a fine-grained multi-class object counting dataset, named KRGRUIDAE, which contains endangered red-crowned crane and white-naped crane in the family Gruidae. We also propose a specialized network for multi-class object counting and line segment density maps, and show their effectiveness by comparing results of existing crowd counting methods on the KR-GRUIDAE dataset
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
GO Barometer: meer wantrouwen en onvoldoende capaciteit binnen het vakgebied
No full textDe tweede editie van de GO Barometer is uit! De Stichting Kennis Gebiedsontwikkeling (SKG) brengt ook dit jaar de stand van zaken binnen het vakgebied van gebiedsontwikkeling in kaart. Gebiedsontwikkeling is een zaak van lange adem, dus er zijn veel overeenkomsten met 2022 – maar toch ook enkele opvallende verschillen. Vooral het stijgende onderlinge wantrouwen tussen partijen is opvallend. Daarnaast zet onvoldoende personele capaciteit de uitvoering van uitdagende ruimtelijke projecten verder onder druk.Urban Development ManagementPractice Chair Urban Area Developmen
Before I Let Go
No full textFront Cover -- Title Page -- Copyright -- Day One -- Midnight Flight -- A Land of Gold and Loneliness -- Stars and Stories -- Unpredictable -- Strangers, Traitors, Ghosts -- Framed Moments -- Loss -- Saints and Sourdough -- Doorways -- The Lonely Lake -- Memories of Infinity -- In the Company of Others -- Foreseen and Foretold -- Whispers in the Night -- Day Two -- Astronomical Twilight -- We Can Be Heroes -- Conversations -- The Choices We Make -- A New Lost -- Happily Sometimes -- Now Here's to You -- Planting Seeds -- To Those We Have Loved and Lost -- Pathways -- Abandon Hope -- Gifts -- Day Three -- Wholesome Lives and Hot Springs -- Birds with Broken Wings -- A Shrine of Blossoms -- Keeper of the Spa -- Writing on the Wall -- Nightmares -- The Way the World Changes -- Do You Understand Now? -- Fear Her -- Of the Dead, Nothing but Good -- No Need to Say Goodbye -- Scorn and Celebration -- Service, Interrupted -- Darkness Falls -- A Backback Full of Home -- The Smell of Smoke -- The Taste of Ashes -- Day Four -- Where Do We Go From Here? -- Polar Twilight -- Night Swimming -- Testimony -- A Cure for All Ills -- Fear about Town -- Empty Rooms, Lost Words -- Dear Diary -- History -- Allies -- Unexpected Friendship -- Northern Lights -- Day Five -- The Smell of Changing Weather -- Understanding Dawns -- Top of the Morning -- The Art of Living -- Stealing In -- The Art of Dying -- The Mist, the Woods, the Darkness -- Kyra vs. the Rest of the World -- Belonging -- Brushstrokes -- Let Me Tell You a Story -- Stolen Time -- The Way the World Ends -- Endless Night -- Endless Day -- Come to Steal Your Soul Away -- Saving the World -- Day Six -- Hero Days -- Homeward Bound -- All the Lives We Shared -- Author's Note -- Acknowledgments -- A Conversation with the Author -- About the Author -- Back CoverDescription based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
검증 가능하게 강건한 뉴럴 네트워크를 위한 훈련 과정 재고
No full text학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2022.2,[iii, 37 p. :]Adversarial examples which are imperceptibly crafted by adversarial attacks can fool neural networks. Defense methods for it have been proposed, but new and stronger attacks can threaten existing defenses. This possibility highlights the importance of certified defense methods that train deep neural networks with verifiably robust guarantees. Interval bound propagation (IBP)-based methods have been demonstrated to be most effective for certified defense, However, we observe that these methods are suffered from Low Epsilon Overfitting (LEO), a problem arising from their training schedule which increases the input perturbation bound (). In this paper, we show that LEO can disturb the learning of a simple linear classifier in higher epsilon and investigate the evidence of LEO by experiments. Based on these observations, we propose a new training strategy, BatchMix, which mixes various in a mini-batch to alleviate LEO. Experimental results on MNIST and CIFAR-10 datasets show that BatchMix can improve the performance of IBP-based methods.한국과학기술원 :전기및전자공학부
GO Barometer ’22: Integrale gebiedsontwikkeling vereist meer capaciteit en innovatie
No full textMet de eerste editie van de GO Barometer bracht de SKG dit voorjaar in kaart wat de stand van zaken is in het vakgebied van gebiedsontwikkeling. In dit artikel bespreken we de vijf belangrijkste inzichten uit de barometer en de discussie daarover tijdens het SKG Jaarcongres eind maart.Urban Development ManagementPractice Chair Urban Area Developmen
Distributive concerns when replacing a pay-as-you-go system with a fully funded system
Get PDFThe author uses a simulation model to quantify the impact on income distribution of having a neutral social security program that is fully funded replace a progressive social security program that redistributes income toward the poor but is financed by a pay-as-you-go method. He finds that if the original pay-as-you-go system is large enough to yield an income replacement rate of at least 40 percent for the middle class and 200 percent for the poor, then the proposed change helps the poor in the long run, so long as public debt does not increase by more than 40 percent of GDP during the transition. Such a reform allows an increase in the capital stock per worker, so in the long run the poor benefit more through higher real wages than they lose because progressive redistribution has ended. In the short run, however, a compensatory program is needed because the poor lose their subsidy before receiving the long-term benefit. In most cases, the 40 percent of GDP available from the increase in public debt is enough to finance a transfer program that compensates the poor in the"short"run (the first 50 years). The author concludes that concern about the welfare of the poor is unwarranted, in both the short and long runs, if the compensatory program is implemented.Environmental Economics&Policies,Economic Theory&Research,Safety Nets and Transfers,Services&Transfers to Poor,Rural Poverty Reduction
Japanese Dialect Ideology from Meiji to the Present
Get PDFThe intent of this study is to examine the trajectory of ideology regarding standard Japanese and dialects from the historical perspective, and also to discuss the cause of the post-war shift of the ideology. Before the war, the government attempted to disseminate hyojun-go aiming at creating a unified Japan in the time when many countries were developing to be nation states after industrial revolution. After the Pacific war, the less strict-sounding term kyotsu-go was more often used, conveying an ideology of democratization. Yet despite the difference in the terms, speaking a common language continues to play a role of unifying the country.
Today there is great interest in regional dialects in Japan. Although kyotsu-go is the common language, most people, especially in urban areas, are familiar with (if not fluent in) kyotsu-go. Due to the development of media and mobilization there are few people who cannot understand kyotsu-go. However, until around the 1970s people were more likely to believe in the superiority of standard Japanese (hyojun-go). Standard language was believed to be superior as a result of language policy that had its origins in Meiji and lasted through WWII. This included education policy that required school children to learn hyojun-go. After the war, in a process of democratization there emerged greater acceptance of language variety: dialect. Thus, there has been a shift in language ideology in Japan, and the people\u27s interests in dialects is one indicator of this. This shift is analyzed here from the perspective of Bourdieu\u27s notion of social and linguistic capital, tying it to policy, historical events and societal change
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