5 citations · 16 across the 4 of their papers we have counts for
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cs.CV2021★ 1 cited
A Decomposition Model for Stereo Matching
Chengtang Yao, Yunde Jia, Huijun Di +2
In this paper, we present a decomposition model for stereo matching to solve the problem of excessive growth in computational cost (time and memory cost) as the resolution increase…
cs.CV2020★ 5 cited
Content-Aware Inter-Scale Cost Aggregation for Stereo Matching
Chengtang Yao, Yunde Jia, Huijun Di +2
Cost aggregation is a key component of stereo matching for high-quality depth estimation. Most methods use multi-scale processing to downsample cost volume for proper context infor…
cs.CV2017★ 5 cited
Learning a Robust Representation via a Deep Network on Symmetric Positive Definite Manifolds
Zhi Gao, Yuwei Wu, Xingyuan Bu +1
Recent studies have shown that aggregating convolutional features of a pre-trained Convolutional Neural Network (CNN) can obtain impressive performance for a variety of visual task…