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

The Mechanism of Copperâ Catalyzed Trifunctionalization of Terminal Allenes

A highly selective copperâ catalyzed trifunctionalization of allenes has been established based on diborylation/cyanation with bis(pinacolato)diboron (B2pin2) and Nâ cyanoâ Nâ phenylâ pâ toluenesulfonamide (NCTS). The Cuâ catalyzed trifunctionalization of terminal allenes is composed of three catalytic reactions (first borocupration, electrophilic cyanation, and second borocupration) that provide a densely functionalized product with regioâ , chemoâ and diastereoselectivity. Allene substrates have multiple reactionâ sites, and the selectivities are determined by the suitable interactions (e.g., electronic and steric demands) between the catalyst and substrates. We employed DFT calculations to understand the cascade copperâ catalyzed trifunctionalization of terminal allenes, providing denselyâ functionalized organic molecules with outstanding regioâ , chemoâ and diastereoselectivity in high yields. The selectivity challenges presented by cumulated Ï â systems are addressed by systematic computational studies; these give insight to the catalytic multipleâ functionalization strategies and explain the high selectivities that we see for these reactions.Cuâ catalyzed trifunctionalization of terminal allenes, through three catalytic reactions (borocupration, electrophilic cyanation, followed by a second borocupration), provides a densely functionalized product with regioâ , chemoâ and diastereoselectivity (see figure). Density functional theory calculations help to understand the cascade catalytic mechanism.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150512/1/chem201900673.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150512/2/chem201900673-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150512/3/chem201900673_am.pd

The Mechanism of Copperâ Catalyzed Trifunctionalization of Terminal Allenes

A highly selective copperâ catalyzed trifunctionalization of allenes has been established based on diborylation/cyanation with bis(pinacolato)diboron (B2pin2) and Nâ cyanoâ Nâ phenylâ pâ toluenesulfonamide (NCTS). The Cuâ catalyzed trifunctionalization of terminal allenes is composed of three catalytic reactions (first borocupration, electrophilic cyanation, and second borocupration) that provide a densely functionalized product with regioâ , chemoâ and diastereoselectivity. Allene substrates have multiple reactionâ sites, and the selectivities are determined by the suitable interactions (e.g., electronic and steric demands) between the catalyst and substrates. We employed DFT calculations to understand the cascade copperâ catalyzed trifunctionalization of terminal allenes, providing denselyâ functionalized organic molecules with outstanding regioâ , chemoâ and diastereoselectivity in high yields. The selectivity challenges presented by cumulated Ï â systems are addressed by systematic computational studies; these give insight to the catalytic multipleâ functionalization strategies and explain the high selectivities that we see for these reactions.Cuâ catalyzed trifunctionalization of terminal allenes, through three catalytic reactions (borocupration, electrophilic cyanation, followed by a second borocupration), provides a densely functionalized product with regioâ , chemoâ and diastereoselectivity (see figure). Density functional theory calculations help to understand the cascade catalytic mechanism.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150512/1/chem201900673.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150512/2/chem201900673-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150512/3/chem201900673_am.pd

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

Inkjet-Printed Silver CPW with Narrow Gap

Inkjet-printed silver coplanar waveguide on a glass substrate with narrow gap is firstly realized by using a selective surface treatment. The measured gap between signal and ground is 16.7 mm. Insertion loss is measured to be 2.04 dB/cm and 4.40 dB/cm at 10 GHz and 40 GHz, respectively

Differentially Expressed Potassium Channels Are Associated with Function of Human Effector Memory CD8+T cells

The voltage-gated potassium channel, Kv1.3, and the Ca2+-activated potassium channel, KCa3.1, regulate membrane potentials in T cells, thereby controlling T cell activation and cytokine production. However, little is known about the expression and function of potassium channels in human effector memory ( EM) CD8+ T cells that can be further divided into functionally distinct subsets based on the expression of the interleukin ( IL)-7 receptor alpha ( IL-7R alpha) chain. Herein, we investigated the functional expression and roles of Kv1.3 and KCa3.1 in EM CD8+ T cells that express high or low levels of the IL-7 receptor alpha chain ( IL-7R alpha(high) and IL-7R alpha(low), respectively). In contrast to the significant activity of Kv1.3 and KCa3.1 in IL-7Rahigh EM CD8+ T cells, IL-7Ralow EM CD8+ T cells showed lower expression of Kv1.3 and insignificant expression of KCa3.1. Kv1.3 was involved in the modulation of cell proliferation and IL-2 production, whereas KCa3.1 affected the motility of EM CD8+ T cells. The lower motility of IL-7Ralow EM CD8+ T cells was demonstrated using transendothelial migration and motility assays with intercellular adhesion molecule 1-and/or chemokine stromal cell-derived factor-1 alpha-coated surfaces. Consistent with the lower migration property, IL-7Ralow EM CD8+ T cells were found less frequently in human skin. Stimulating IL-7Ralow EM CD8+ T cells with IL-2 or IL-15 increased their motility and recovery of KCa3.1 activity. Our findings demonstrate that Kv1.3 and KCa3.1 are differentially involved in the functions of EM CD8+ T cells. The weak expression of potassium channels in IL-7Ralow EM CD8+ T cells can be revived by stimulation with IL-2 or IL-15, which restores the associated functions. This study suggests that IL-7Rahigh EM CD8+ T cells with functional potassium channels may serve as a reservoir for effector CD8+ T cells during peripheral inflammation.112Ysciescopu