517 research outputs found
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 CopperĆ¢ Catalyzed Trifunctionalization of Terminal Allenes
A highly selective copperĆ¢ catalyzed trifunctionalization of allenes has been established based on diborylation/cyanation with bis(pinacolato)diboron (B2pin2) and NĆ¢ cyanoĆ¢ NĆ¢ phenylĆ¢ pĆ¢ toluenesulfonamide (NCTS). The CuĆ¢ 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 regioĆ¢ , chemoĆ¢ and diastereoselectivity. Allene substrates have multiple reactionĆ¢ 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 copperĆ¢ catalyzed trifunctionalization of terminal allenes, providing denselyĆ¢ functionalized organic molecules with outstanding regioĆ¢ , chemoĆ¢ and diastereoselectivity in high yields. The selectivity challenges presented by cumulated Ć Ć¢ systems are addressed by systematic computational studies; these give insight to the catalytic multipleĆ¢ functionalization strategies and explain the high selectivities that we see for these reactions.CuĆ¢ catalyzed trifunctionalization of terminal allenes, through three catalytic reactions (borocupration, electrophilic cyanation, followed by a second borocupration), provides a densely functionalized product with regioĆ¢ , chemoĆ¢ 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 CopperĆ¢ Catalyzed Trifunctionalization of Terminal Allenes
A highly selective copperĆ¢ catalyzed trifunctionalization of allenes has been established based on diborylation/cyanation with bis(pinacolato)diboron (B2pin2) and NĆ¢ cyanoĆ¢ NĆ¢ phenylĆ¢ pĆ¢ toluenesulfonamide (NCTS). The CuĆ¢ 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 regioĆ¢ , chemoĆ¢ and diastereoselectivity. Allene substrates have multiple reactionĆ¢ 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 copperĆ¢ catalyzed trifunctionalization of terminal allenes, providing denselyĆ¢ functionalized organic molecules with outstanding regioĆ¢ , chemoĆ¢ and diastereoselectivity in high yields. The selectivity challenges presented by cumulated Ć Ć¢ systems are addressed by systematic computational studies; these give insight to the catalytic multipleĆ¢ functionalization strategies and explain the high selectivities that we see for these reactions.CuĆ¢ catalyzed trifunctionalization of terminal allenes, through three catalytic reactions (borocupration, electrophilic cyanation, followed by a second borocupration), provides a densely functionalized product with regioĆ¢ , chemoĆ¢ 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
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