Search Results for author:
Found 13 papers, 6 papers with code
MotionAug: Augmentation with Physical Correction for Human Motion Prediction
Our IK-based motion synthesis method allows us to generate a variety of motions semi-automatically.
Group Activity Recognition Using Joint Learning of Individual Action Recognition and People Grouping
This paper proposes joint learning of individual action recognition and people grouping for improving group activity recognition.
Ranked #5 on
Group Activity Recognition
on Volleyball
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results
This paper reviews the NTIRE2021 challenge on burst super-resolution.
AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results
Missing information can be restored well in this region, especially in HR videos, where the high-frequency content mostly consists of texture details.
Image Super-Resolution using Explicit Perceptual Loss
The previous approaches use several loss functions which is hard to interpret and has the implicit relationships to improve the perceptual score.
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results.
Space-Time-Aware Multi-Resolution Video Enhancement
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.
Semi- and Weakly-supervised Human Pose Estimation
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.
Deep Back-Projection Networks for Single Image Super-resolution
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.
Ranked #1 on
Image Super-Resolution
on BSDS100 - 8x upscaling
Recurrent Back-Projection Network for Video Super-Resolution
We proposed a novel architecture for the problem of video super-resolution.
Human Pose Estimation using Motion Priors and Ensemble Models
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).
Task-Driven Super Resolution: Object Detection in Low-resolution Images
We consider how image super resolution (SR) can contribute to an object detection task in low-resolution images.
Deep Back-Projection Networks For Super-Resolution
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.
Ranked #14 on
Video Super-Resolution
on Vid4 - 4x upscaling
