64 citations · 130 across the 6 of their papers we have counts for
Showing 2016Show all
3 papers · 1 filter
cs.CV2016★ 3 cited
From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blur
Dong Gong, Jie Yang, Lingqiao Liu +5
Removing pixel-wise heterogeneous motion blur is challenging due to the ill-posed nature of the problem. The predominant solution is to estimate the blur kernel by adding a prior,…
cs.CV2016★ 5 cited
Attend in groups: a weakly-supervised deep learning framework for learning from web data
Bohan Zhuang, Lingqiao Liu, Yao Li +2
Large-scale datasets have driven the rapid development of deep neural networks for visual recognition. However, annotating a massive dataset is expensive and time-consuming. Web im…
cs.CV2016★ 64 cited
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Guosheng Lin, Anton Milan, Chunhua Shen +1
Recently, very deep convolutional neural networks (CNNs) have shown outstanding performance in object recognition and have also been the first choice for dense classification probl…