Search Results for author:
Found 7 papers, 5 papers with code
Object-Centric Multi-Task Learning for Human Instances
Human is one of the most essential classes in visual recognition tasks such as detection, segmentation, and pose estimation.
Real-Time Video Deblurring via Lightweight Motion Compensation
While motion compensation greatly improves video deblurring quality, separately performing motion compensation and video deblurring demands huge computational overhead.
Iterative Filter Adaptive Network for Single Image Defocus Deblurring
We propose a novel end-to-end learning-based approach for single image defocus deblurring.
Ranked #3 on
Image Defocus Deblurring
on RealDOF
Recurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes
To alleviate this problem, we propose two novel approaches to deblur videos by effectively aggregating information from multiple video frames.
Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions
To utilize the property with inverse kernels, we exploit the observation that when only the size of a defocus blur changes while keeping the shape, the shape of the corresponding inverse kernel remains the same and only the scale changes.
Ranked #8 on
Image Defocus Deblurring
on DPD
Deep Color Transfer using Histogram Analogy
We propose a novel approach to transferring the color of a reference image to a given source image.
SRFeat: Single Image Super-Resolution with Feature Discrimination
Generative adversarial networks (GANs) have recently been adopted to single image super resolution (SISR) and showed impressive results with realistically synthesized high-frequency textures.
