TL;DR
An improved algorithm based on dynamic multi-feature fusion and dual-branch adaptive aggregation that adapts to local scene characteristics and the ultimate disparity map is generated through a region-based disparity optimization module and multiple optimization processes.
A dense matching network based on a Transformer and multi-scale feature fusion, called Task-aware Multi-Scale Matching Network (TMSMNet) is proposed, which outperforms mainstream methods such as RAFT-Stereo on the D1-all metric of KITTI- 2015 and demonstrates good generalization and robustness.
To address the insufficient matching accuracy of traditional stereo matching in areas with weak textures, low contrast, and edges of millimeter-scale miniature components, this article proposes a binocular 3-D reconstruction method for visible surfaces based on adaptive multi-interpolation and multidimensional feature...
To address central pixel dependency and degraded matching reliability in low-texture or occluded regions, this paper proposes a robust binocular ranging framework integrating an improved Census-BT cost with a multi-resolution region of interest (ROI) pyramid strategy. The approach employs an annular Gaussian-weighted C...
In recent years, binocular stereo matching has been widely adopted for three-dimensional object measurement. However, conventional methods often suffer from performance degradation in close-range scenarios, where the reduced distance to the target results in substantially larger disparities, requiring a wider search ra...
This paper proposes a robust feature-based matching framework that reduces reliance on intensity information while enhancing structural representation and demonstrates that MIHOG can provide dense and reliable correspondences under complex cross-modal radiometric and geometric variations.
In vision-based industrial quality inspection, uneven illumination, specular reflection, and coating inconsistencies often cause unsupervised segmentation methods to suffer from over-segmentation and erroneous region merging. To address this problem, this paper proposes an adaptive dual-granularity consensus manifold f...
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