332 citations · 994 across the 17 of their papers we have counts for
18 papers
Spatial-Temporal Space Hand-in-Hand: Spatial-Temporal Video Super-Resolution via Cycle-Projected Mutual Learning
Mengshun Hu, Kui Jiang, Liang Liao +3
Spatial-Temporal Video Super-Resolution (ST-VSR) aims to generate super-resolved videos with higher resolution(HR) and higher frame rate (HFR). Quite intuitively, pioneering two-st…
Asymmetric Loss Functions for Learning with Noisy Labels
Xiong Zhou, Xianming Liu, Junjun Jiang +2
Robust loss functions are essential for training deep neural networks with better generalization power in the presence of noisy labels. Symmetric loss functions are confirmed to be…
BaMBNet: A Blur-aware Multi-branch Network for Defocus Deblurring
Pengwei Liang, Junjun Jiang, Xianming Liu +1
The defocus deblurring raised from the finite aperture size and exposure time is an essential problem in the computational photography. It is very challenging because the blur kern…
Fast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Report
Andrey Ignatov, Grigory Malivenko, David Plowman +35
Depth estimation is an important computer vision problem with many practical applications to mobile devices. While many solutions have been proposed for this task, they are usually…
High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal Fusion
Zhiwei Zhong, Xianming Liu, Junjun Jiang +3
Depth map records distance between the viewpoint and objects in the scene, which plays a critical role in many real-world applications. However, depth map captured by consumer-grad…
Omniscient Video Super-Resolution
Peng Yi, Zhongyuan Wang, Kui Jiang +4
Most recent video super-resolution (SR) methods either adopt an iterative manner to deal with low-resolution (LR) frames from a temporally sliding window, or leverage the previousl…