54 citations · 363 across the 32 of their papers we have counts for
7 papers · 1 filter
MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition
Zhanghan Ke, Jiayu Sun, Kaican Li +2
Existing portrait matting methods either require auxiliary inputs that are costly to obtain or involve multiple stages that are computationally expensive, making them less suitable…
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
Kai Zhang, Martin Danelljan, Yawei Li +75
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an in…
Guided Collaborative Training for Pixel-wise Semi-Supervised Learning
Zhanghan Ke, Di Qiu, Kaican Li +2
We investigate the generalization of semi-supervised learning (SSL) to diverse pixel-wise tasks. Although SSL methods have achieved impressive results in image classification, the…
Hierarchical Regression Network for Spectral Reconstruction from RGB Images
Yuzhi Zhao, Lai-Man Po, Qiong Yan +2
Capturing visual image with a hyperspectral camera has been successfully applied to many areas due to its narrow-band imaging technology. Hyperspectral reconstruction from RGB imag…
NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte +87
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new versi…
NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image
Boaz Arad, Radu Timofte, Ohad Ben-Shahar +4
This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. As…
Polarized Reflection Removal with Perfect Alignment in the Wild
Chenyang Lei, Xuhua Huang, Mengdi Zhang +3
We present a novel formulation to removing reflection from polarized images in the wild. We first identify the misalignment issues of existing reflection removal datasets where the…