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Found 4 papers, 1 papers with code
FastMESH: Fast Surface Reconstruction by Hexagonal Mesh-based Neural Rendering
Despite the promising results of multi-view reconstruction, the recent neural rendering-based methods, such as implicit surface rendering (IDR) and volume rendering (NeuS), not only incur a heavy computational burden on training but also have the difficulties in disentangling the geometric and appearance.
Multi-View Stereo Representation Revisit: Region-Aware MVSNet
Comparing to the conventional deep learning-based multi-view stereo methods, our proposed RA-MVSNet approach obtains more complete reconstruction results by taking advantage of signed distance supervision.
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Multi-View Stereo Representation Revist: Region-Aware MVSNet
It is essential to the textureless regions and surface boundary that cannot be properly reconstructed. To address this issue, we suggest to take advantage of point-to-surface distance so that the model is able to perceive a wider range of surfaces.
Multiview Textured Mesh Recovery by Differentiable Rendering
Although having achieved the promising results on shape and color recovery through self-supervision, the multi-layer perceptrons-based methods usually suffer from heavy computational cost on learning the deep implicit surface representation.
