1,808 research outputs found

    CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering

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    Intrinsic image decomposition is a challenging, long-standing computer vision problem for which ground truth data is very difficult to acquire. We explore the use of synthetic data for training CNN-based intrinsic image decomposition models, then applying these learned models to real-world images. To that end, we present \ICG, a new, large-scale dataset of physically-based rendered images of scenes with full ground truth decompositions. The rendering process we use is carefully designed to yield high-quality, realistic images, which we find to be crucial for this problem domain. We also propose a new end-to-end training method that learns better decompositions by leveraging \ICG, and optionally IIW and SAW, two recent datasets of sparse annotations on real-world images. Surprisingly, we find that a decomposition network trained solely on our synthetic data outperforms the state-of-the-art on both IIW and SAW, and performance improves even further when IIW and SAW data is added during training. Our work demonstrates the suprising effectiveness of carefully-rendered synthetic data for the intrinsic images task.Comment: Paper for 'CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering' published in ECCV, 201

    Previous Examination - An Analysis of its Applicability

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    The objective of this article is to demonstrate, besides the phatic crisis of the Brazilian economy, the function, the applicability and limits to the power conceived by Law to the Judge when designating the Previous Examination on the proceedings of Judicial Reorganization and also to demonstrate the influences that this may cause in its factual and legal aspects. Before entering the practical aspects of the Previous Examination, it is necessary a brief contextualisation about the economic crisis in Brazil and also an analysis of the Judicial Reorganization as a mechanism to overcome the economic and financial crises which are affecting Brazilian Companies. Using a historical and legal background, this article analyzes practical aspects of the Previous Examination and its effectiveness in improving the proceedings by verifying the empirical data when deciding whether to rule in favor of the Judicial Reorganization

    An Improved Groundwater Model Framework for Aquifer Structures of the Quaternary-Formed Sediment Body in the Southernmost Parts of the Mekong Delta, Vietnam

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    The Ca Mau peninsula (CMP) is a key economic region in southern Vietnam. In recent decades, the high demand for water has increased the exploitation of groundwater, thus lowering the groundwater level and leading to risks of degradation, depletion, and land subsidence, as well as salinity intrusion in the groundwater of the whole Mekong Delta region. By using a finite element groundwater model with boundary expansion to the sea, we updated the latest data on hydrogeological profiles, groundwater levels, and exploitation. The basic model setup covers seven aquifers and seven aquitards. It is determined that the inflow along the coastline to the mainland is 39% of the total inflow. The exploitation of the study area in 2019 was 567,364 m3/day. The most exploited aquifers are the upper-middle Pleistocene (qp2–3) and the middle Pliocene (n22), accounting for 63.7% and 24.6%, respectively; the least exploited aquifers are the upper Pleistocene and the upper Miocene, accounting for 0.35% and 0.02%, respectively. In the deeper aquifers, qp2–3 and n22, the change in storage is negative due to the high exploitation rate, leading to a decline in the reserves of these aquifers. These groundwater model results are the calculations of groundwater reserves from the coast to the mainland in the entire system of aquifers in the CMP. This makes groundwater decision managers, stakeholders, and others more efficient in sustainable water resources planning in the CMP and Mekong Delta (MKD)
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