Generalized Video Deblurring for Dynamic Scenes

Several state-of-the-art video deblurring methods are based on a strong assumption that the captured scenes are static. These methods fail to deblur blurry videos in dynamic scenes. We propose a video deblurring method to deal with general blurs inherent in dynamic scenes, contrary to other methods. To handle locally varying and general blurs caused by various sources, such as camera shake, moving objects, and depth variation in a scene, we approximate pixel-wise kernel with bidirectional optical flows. Therefore, we propose a single energy model that simultaneously estimates optical flows and latent frames to solve our deblurring problem. We also provide a framework and efficient solvers to optimize the energy model. By minimizing the proposed energy function, we achieve significant improvements in removing blurs and estimating accurate optical flows in blurry frames. Extensive experimental results demonstrate the superiority of the proposed method in real and challenging videos that state-of-the-art methods fail in either deblurring or optical flow estimation.Comment: CVPR 2015 ora

Online Video Deblurring via Dynamic Temporal Blending Network

State-of-the-art video deblurring methods are capable of removing non-uniform blur caused by unwanted camera shake and/or object motion in dynamic scenes. However, most existing methods are based on batch processing and thus need access to all recorded frames, rendering them computationally demanding and time consuming and thus limiting their practical use. In contrast, we propose an online (sequential) video deblurring method based on a spatio-temporal recurrent network that allows for real-time performance. In particular, we introduce a novel architecture which extends the receptive field while keeping the overall size of the network small to enable fast execution. In doing so, our network is able to remove even large blur caused by strong camera shake and/or fast moving objects. Furthermore, we propose a novel network layer that enforces temporal consistency between consecutive frames by dynamic temporal blending which compares and adaptively (at test time) shares features obtained at different time steps. We show the superiority of the proposed method in an extensive experimental evaluation.Comment: 10 page

Measuring Willingness to Accept for GM Food by Characteristics

Korean consumers' willingness to accept (WTA) for GM food are studied in this paper. This study compares hypothetical and nonhypothetical responses to choice experiment questions. We test for hypothetical bias in a choice experiment involving GM rice with differing characteristic attributes and multinomial logit model is applied to predict the estimated results. In general, hypothetical responses predicted higher probabilities of purchasing GM rice than nonhypothetical responses. Thus, hypothetical choices overestimate willingness to accept for GM rice. The results of this paper could contributes to government's GM food policies and subsequent studies, also improving economic welfare of farmers and consumers.GM Food, Willingness to Accept, Choice experiment, Hypothetical bias, Food Consumption/Nutrition/Food Safety,

Blending Machine and Human Learning Processes

Citizen science projects face a dilemma in relying on contributions from volunteers to achieve their scientific goals: providing volunteers with explicit training might increase the quality of contributions, but at the cost of losing the work done by newcomers during the training period, which for many is the only work they will contribute to the project. Based on research in cognitive science on how humans learn to classify images, we have designed an approach to use machine learning to guide the presentation of tasks to newcomers that help them more quickly learn how to do the image classification task while still contributing to the work of the project. A Bayesian model for tracking volunteer learning is presented

Scene-Adaptive Video Frame Interpolation via Meta-Learning

Video frame interpolation is a challenging problem because there are different scenarios for each video depending on the variety of foreground and background motion, frame rate, and occlusion. It is therefore difficult for a single network with fixed parameters to generalize across different videos. Ideally, one could have a different network for each scenario, but this is computationally infeasible for practical applications. In this work, we propose to adapt the model to each video by making use of additional information that is readily available at test time and yet has not been exploited in previous works. We first show the benefits of `test-time adaptation' through simple fine-tuning of a network, then we greatly improve its efficiency by incorporating meta-learning. We obtain significant performance gains with only a single gradient update without any additional parameters. Finally, we show that our meta-learning framework can be easily employed to any video frame interpolation network and can consistently improve its performance on multiple benchmark datasets.Comment: CVPR 202

Imaging findings of mimickers of hepatocellular carcinoma

Radiological imaging plays a crucial role in the diagnosis of hepatocellular carcinoma (HCC) as the noninvasive diagnosis of HCC in high-risk patients by typical imaging findings alone is widely adopted in major practice guidelines for HCC. While imaging techniques have markedly improved in detecting small liver lesions, they often detect incidental benign liver lesions and non-hepatocellular malignancy that can be misdiagnosed as HCC. The most common mimicker of HCC in cirrhotic liver is nontumorous arterioportal shunts that are seen as focal hypervascular liver lesions on dynamic contrast-enhanced cross-sectional imaging. Rapidly enhancing hemangiomas can be easily misdiagnosed as HCC especially on MR imaging with liver-specific contrast agent. Focal inflammatory liver lesions mimic HCC by demonstrating arterial-phase hypervascularity and subsequent washout on dynamic contrast-enhanced imaging. It is important to recognize the suggestive imaging findings for intrahepatic cholangiocarcinoma (CC) as the management of CC is largely different from that of HCC. There are other benign mimickers of HCC such as angiomyolipomas and focal nodular hyperplasia-like nodules. Recognition of their typical imaging findings can reduce false-positive HCC diagnosis

Successful Magnetic Resonance Imaging-Guided Focused Ultrasound Surgery for Recurrent Uterine Fibroid Previously Treated with Uterine Artery Embolization

A 45-year-old premenopausal woman was referred to our clinic due to recurring symptoms of uterine fibroids, nine years after a uterine artery embolization (UAE). At the time of screening, the patient presented with bilateral impairment and narrowing of the uterine arteries, which increased the risk of arterial perforation during repeated UAE procedures. The patient was subsequently referred for magnetic resonance imaging-guided focused ultrasound surgery (MRgFUS) treatment. Following the treatment, the patient experienced a significant improvement in symptoms (symptom severity score was reduced from 47 to 12 by 1 year post-treatment). MR images at 3 months showed a 49% decrease in fibroid volume. There were no adverse events during the treatment or the follow-up period. This case suggests that MRgFUS can be an effective treatment option for patients with recurrent fibroids following previous UAE treatment

Disc haemorrhage associated with an enlarged peripapillary intrachoroidal cavitation in a non-glaucomatous myopic eye: a case report

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Abstract Background Disc haemorrhage (DH) is considered a characteristic sign of glaucoma, but its causative mechanism remains to be determined. We present a case of DH that occurred in association with an enlarged peripapillary intrachoroidal cavitation in a non-glaucomatous eye. Case presentation A 35-year-old woman was evaluated for a DH that had been detected during a preoperative examination for myopic refractive surgery. Enhanced depth imaging spectral-domain optical coherence tomography imaging of the optic nerve revealed a peripapillary intrachoroidal cavitation adjacent to the DH. The DH was also present at the 1-year follow-up, but had been completely absorbed at the 2-year follow-up, respectively with an enlargement and shrinkage of the intrachoroidal cavitation and prelaminar tissue schisis. Glaucomatous optic nerve change was not observed during the entire follow-up. Conclusion DH can be caused by mechanical damage to capillaries from microscopic changes in peripapillary tissues such as enlargement of the intrachoroidal cavitation, regardless of the presence of glaucoma