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Found 5 papers, 1 papers with code
Improved Neural Radiance Fields Using Pseudo-depth and Fusion
To make the constructed volumes as close as possible to the surfaces of objects in the scene and the rendered depth more accurate, we propose to perform depth prediction and radiance field reconstruction simultaneously.
SDFReg: Learning Signed Distance Functions for Point Cloud Registration
We then propose to alternately optimize the implicit function and the registration between the implicit function and point cloud.
DS-MVSNet: Unsupervised Multi-view Stereo via Depth Synthesis
To mine the information in probability volume, we creatively synthesize the source depths by splattering the probability volume and depth hypotheses to source views.
DepthGAN: GAN-based Depth Generation of Indoor Scenes from Semantic Layouts
Limited by the computational efficiency and accuracy, generating complex 3D scenes remains a challenging problem for existing generation networks.
ACDNet: Adaptively Combined Dilated Convolution for Monocular Panorama Depth Estimation
Depth estimation is a crucial step for 3D reconstruction with panorama images in recent years.
Ranked #5 on
Depth Estimation
on Stanford2D3D Panoramic
