- Image/Video Storage, Retrieval
- Image/Video Processing
- Image/Video Coding
- Image Scanning, Display, and Printing
- Image Formation
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- Read more about CNN-BASED LUMINANCE AND COLOR CORRECTION FOR ILL-EXPOSED IMAGES
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Image restoration and image enhancement are critical image processing tasks since good image quality is mandatory for many image applications. We are particularly interested in the restoration of ill-exposed images. These effects are caused by sensor limitation or optical arrangement. They prevent the details of the scene from being adequately represented in the captured image. We proposed a deep neural network model due to the number of uncontrolled variables that impact the acquisition.
PPT_ICIP.pdf
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- Read more about EMBEDDED CYCLEGAN FOR SHAPE-AGNOSTIC IMAGE-TO-IMAGE TRANSLATION
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- Read more about SHOW, TRANSLATE AND TELL
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Humans have an incredible ability to process and understand
information from multiple sources such as images,
video, text, and speech. Recent success of deep neural
networks has enabled us to develop algorithms which give
machines the ability to understand and interpret this information.
There is a need to both broaden their applicability and
develop methods which correlate visual information along
with semantic content. We propose a unified model which
jointly trains on images and captions, and learns to generate
STT_v5.pdf
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- Read more about MULTI-TASK LEARNING WITH COMPRESSIBLE FEATURES FOR COLLABORATIVE INTELLIGENCE
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A promising way to deploy Artificial Intelligence (AI)-based services on mobile devices is to run a part of the AI model (a deep neural network) on the mobile itself, and the rest in the cloud. This is sometimes referred to as collaborative intelligence. In this framework, intermediate features from the deep network need to be transmitted to the cloud for further processing. We study the case where such features are used for multiple purposes in the cloud (multi-tasking) and where they need to be compressible in order to allow efficient transmission to the cloud.
ICIP_2019.pptx
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- Read more about DEEP UNSUPERVISED LEARNING FOR SIMULTANEOUS VISUAL ODOMETRY AND DEPTH ESTIMATION
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- Read more about IMPRESSION ESTIMATION FOR DEFORMED PORTRAITS WITH A LANDMARK-BASED RANKING NETWORK
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In recent years, it has become a trend for people to manipulate their own portraits before posting them on a social networking service. However, it is difficult to get a desired portrait after manipulation without sufficient experience or skill. To obtain a simpler and more effective portrait manipulation technique, we consider an automated portrait manipulation method based on five impression words: clear, sweet, elegant, modern, and dynamic.
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- Read more about MULTIMODAL LATENT FACTOR MODEL WITH LANGUAGE CONSTRAINT FOR PREDICATE DETECTION
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poster-2.pdf
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- Read more about Multimodal Point Distribution Model for Anthropological Landmark Detection
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While current landmark detection algorithms offer a good approximation of the landmark locations, they are often unsuitable for the use in biological research. We present multimodal landmark detection approach, based on Point distribution model that detects a larger number of anthropologically relevant landmarks than the current landmark detection algorithms.
At the same time we show that improving detection accuracy of initial vertices, using image information, to which
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