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Found 5 papers, 2 papers with code
H&E Stain Normalization using U-Net
We also compared to StainNet and found that our method delivered quantitatively and qualitatively better results.
GPR-Net: Multi-view Layout Estimation via a Geometry-aware Panorama Registration Network
The major improvement over PSMNet comes from a novel Geometry-aware Panorama Registration Network or GPR-Net that effectively tackles the wide baseline registration problem by exploiting the layout geometry and computing fine-grained correspondences on the layout boundaries, instead of the global pixel-space.
High-Resolution Depth Estimation for 360-degree Panoramas through Perspective and Panoramic Depth Images Registration
We propose a novel approach to compute high-resolution (2048x1024 and higher) depths for panoramas that is significantly faster and qualitatively and qualitatively more accurate than the current state-of-the-art method (360MonoDepth).
Manhattan Room Layout Reconstruction from a Single 360 image: A Comparative Study of State-of-the-art Methods
Recent approaches for predicting layouts from 360 panoramas produce excellent results.
DuLa-Net: A Dual-Projection Network for Estimating Room Layouts from a Single RGB Panorama
We present a deep learning framework, called DuLa-Net, to predict Manhattan-world 3D room layouts from a single RGB panorama.
