21 citations · 26 across the 2 of their papers we have counts for
2 papers
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.CV2018★ 21 cited
Deep Stereo Matching with Explicit Cost Aggregation Sub-Architecture
Lidong Yu, Yucheng Wang, Yuwei Wu +1
Deep neural networks have shown excellent performance for stereo matching. Many efforts focus on the feature extraction and similarity measurement of the matching cost computation…