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Found 6 papers, 3 papers with code
Gated Cross-Attention Network for Depth Completion
With a simple yet efficient gating mechanism, our proposed method achieves fast and accurate depth completion without the need for additional branches or post-processing steps.
Pseudo-label Correction and Learning For Semi-Supervised Object Detection
Our proposed method, Pseudo-label Correction and Learning (PCL), is extensively evaluated on the MS COCO and PASCAL VOC benchmarks.
Multi-Scale Cost Volumes Cascade Network for Stereo Matching
This is because different cost volumes play a crucial role in balancing speed and accuracy.
Parallax Attention for Unsupervised Stereo Correspondence Learning
Based on our PAM, we propose a parallax-attention stereo matching network (PASMnet) and a parallax-attention stereo image super-resolution network (PASSRnet) for stereo matching and stereo image super-resolution tasks.
Learning Parallax Attention for Stereo Image Super-Resolution
Stereo image pairs can be used to improve the performance of super-resolution (SR) since additional information is provided from a second viewpoint.
Ranked #1 on
Image Super-Resolution
on KITTI 2012 - 4x upscaling
Learning for Disparity Estimation through Feature Constancy
The second part performs matching cost calculation, matching cost aggregation and disparity calculation to estimate the initial disparity using shared features.
