61 citations · 352 across the 38 of their papers we have counts for
9 papers · 1 filter
iShape: A First Step Towards Irregular Shape Instance Segmentation
Lei Yang, Yan Zi Wei, Yisheng HE +4
In this paper, we introduce a brand new dataset to promote the study of instance segmentation for objects with irregular shapes. Our key observation is that though irregularly shap…
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results
Goutam Bhat, Martin Danelljan, Radu Timofte +25
This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times hig…
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
Zhen Liu, Wenjie Lin, Xinpeng Li +6
In this paper, we present an attention-guided deformable convolutional network for hand-held multi-frame high dynamic range (HDR) imaging, namely ADNet. This problem comprises two…
Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report
Andrey Ignatov, Kim Byeoung-su, Radu Timofte +29
Image denoising is one of the most critical problems in mobile photo processing. While many solutions have been proposed for this task, they are usually working with synthetic data…
Practical Wide-Angle Portraits Correction with Deep Structured Models
Jing Tan, Shan Zhao, Pengfei Xiong +3
Wide-angle portraits often enjoy expanded views. However, they contain perspective distortions, especially noticeable when capturing group portrait photos, where the background is…
ASFlow: Unsupervised Optical Flow Learning with Adaptive Pyramid Sampling
Kunming Luo, Ao Luo, Chuan Wang +2
We present an unsupervised optical flow estimation method by proposing an adaptive pyramid sampling in the deep pyramid network. Specifically, in the pyramid downsampling, we propo…
FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation
Yisheng He, Haibin Huang, Haoqiang Fan +2
In this work, we present FFB6D, a Full Flow Bidirectional fusion network designed for 6D pose estimation from a single RGBD image. Our key insight is that appearance information in…
Motion Basis Learning for Unsupervised Deep Homography Estimation with Subspace Projection
Nianjin Ye, Chuan Wang, Haoqiang Fan +1
In this paper, we introduce a new framework for unsupervised deep homography estimation. Our contributions are 3 folds. First, unlike previous methods that regress 4 offsets for a…
D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution
Youwei Li, Haibin Huang, Lanpeng Jia +2
In this paper, we present D2C-SR, a novel framework for the task of real-world image super-resolution. As an ill-posed problem, the key challenge in super-resolution related tasks…