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Facial Attributes Classification Using Multi-task Representation Learning
This paper presents a new approach for facial attribute classification using a multi-task learning approach. Unlike other approaches that uses hand engineered features, our model learns a sharedExpand
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Deep Residual Learning in the JPEG Transform Domain
  • Max Ehrlich, L. Davis
  • Computer Science, Mathematics
  • IEEE/CVF International Conference on Computer…
  • 31 December 2018
We introduce a general method of performing Residual Network inference and learning in the JPEG transform domain that allows the network to consume compressed images as input. Our formulationExpand
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Stacked U-Nets for Ground Material Segmentation in Remote Sensing Imagery
We present a semantic segmentation algorithm for RGB remote sensing images. Our method is based on the Dilated Stacked U-Nets architecture. This state-of-the-art method has been shown to have goodExpand
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Action-Affect-Gender Classification Using Multi-task Representation Learning
Recent work in affective computing focused on affect from facial expressions, and not as much on body. This work focuses on body affect. Affect does not occur in isolation. Humans usually coupleExpand
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Action-Affect Classification and Morphing using Multi-Task Representation Learning
Most recent work focused on affect from facial expressions, and not as much on body. This work focuses on body affect analysis. Affect does not occur in isolation. Humans usually couple affect withExpand
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Discriminative hand localization in depth images
We present a novel hand localization technique for 3D user interfaces. Our method is designed to overcome the difficulty of fitting anatomical models which fail to converge or converge with largeExpand
Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer
Urban material recognition in remote sensing imagery is a challenging problem due to the difficulty of obtaining human annotations, especially on low resolution satellite images. To this end, weExpand
Quantization Guided JPEG Artifact Correction
The JPEG image compression algorithm is the most popular method of image compression because of its ability for large compression ratios. However, to achieve such high compression, information isExpand