Search Results for author: Norimichi Ukita

Found 13 papers, 6 papers with code

Image Super-Resolution using Explicit Perceptual Loss

no code implementations1 Sep 2020 Tomoki Yoshida, Kazutoshi Akita, Muhammad Haris, Norimichi Ukita

The previous approaches use several loss functions which is hard to interpret and has the implicit relationships to improve the perceptual score.

Image Super-Resolution

Space-Time-Aware Multi-Resolution Video Enhancement

1 code implementation CVPR 2020 Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

We consider the problem of space-time super-resolution (ST-SR): increasing spatial resolution of video frames and simultaneously interpolating frames to increase the frame rate.

Video Enhancement Video Super-Resolution

Semi- and Weakly-supervised Human Pose Estimation

no code implementations4 Jun 2019 Norimichi Ukita, Yusuke Uematsu

While the first and second learning schemes select only poses that are similar to those in the supervised training data, the third scheme selects more true-positive poses that are significantly different from any supervised poses.

Pose Estimation

Deep Back-Projection Networks for Single Image Super-resolution

1 code implementation4 Apr 2019 Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

Previous feed-forward architectures of recently proposed deep super-resolution networks learn the features of low-resolution inputs and the non-linear mapping from those to a high-resolution output.

Image Super-Resolution Single Image Super Resolution

Human Pose Estimation using Motion Priors and Ensemble Models

no code implementations26 Jan 2019 Norimichi Ukita

Human pose estimation in images and videos is one of key technologies for realizing a variety of human activity recognition tasks (e. g., human-computer interaction, gesture recognition, surveillance, and video summarization).

3D Human Pose Tracking Gesture Recognition +3

Task-Driven Super Resolution: Object Detection in Low-resolution Images

no code implementations30 Mar 2018 Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

We consider how image super resolution (SR) can contribute to an object detection task in low-resolution images.

Image Super-Resolution object-detection +1

Deep Back-Projection Networks For Super-Resolution

18 code implementations CVPR 2018 Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

The feed-forward architectures of recently proposed deep super-resolution networks learn representations of low-resolution inputs, and the non-linear mapping from those to high-resolution output.

Image Super-Resolution Video Super-Resolution

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