9,306 research outputs found
Optimal modeling for complex system design
The article begins with a brief introduction to the theory describing optimal data compression systems and their performance. A brief outline is then given of a representative algorithm that employs these lessons for optimal data compression system design. The implications of rate-distortion theory for practical data compression system design is then described, followed by a description of the tensions between theoretical optimality and system practicality and a discussion of common tools used in current algorithms to resolve these tensions. Next, the generalization of rate-distortion principles to the design of optimal collections of models is presented. The discussion focuses initially on data compression systems, but later widens to describe how rate-distortion theory principles generalize to model design for a wide variety of modeling applications. The article ends with a discussion of the performance benefits to be achieved using the multiple-model design algorithms
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
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