Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Evaluation of LDR, tone mapped and HDR stereo matching using cost-volume filtering approach
A framework for HDR stereo matching using multi-exposed images
Local stereo matching algorithm with efficient matching cost and adaptive guided image filter
3D cost aggregation with multiple minimum spanning trees for stereo matching.
On building an accurate stereo matching system on graphics hardware
Fast PatchMatch stereo matching using cross-scale cost fusion for automotive applications
A Deep Visual Correspondence Embedding Model for Stereo Matching Costs
Accurate and efficient stereo processing by semi-global matching and mutual information
Efficient Deep Learning for Stereo Matching
High-Quality Real-Time Stereo Using Adaptive Cost Aggregation and Dynamic Programming
A Computational Framework for Determining Stereo Correspondence from a Set of Linear Spatial Filters
Leveraging stereo matching with learning-based confidence measures
Fast Cost-Volume Filtering for Visual Correspondence and Beyond
Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching
Occlusion and Error Detection for Stereo Matching and Hole-Filling Using Dynamic Programming
Near real-time reliable stereo matching using programmable graphics hardware
Order-Based Disparity Refinement Including Occlusion Handling for Stereo Matching
Semi-global Stereo Matching with Surface Orientation Priors
A Fast Trilateral Filter-Based Adaptive Support Weight Method for Stereo Matching
A Low-Cost Real-Time Embedded Stereo Vision System for Accurate Disparity Estimation Based on Guided Image Filtering
Constant Time Weighted Median Filtering for Stereo Matching and Beyond
Relation classification via modeling augmented dependency paths
Convolutional Neural Networks on 3D Surfaces Using Parallel Frames
Building A Shallow Arabic Morphological Analyser In One Day
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
Fast Feature Pyramids for Object Detection