Surface Normal Estimation

26 papers with code • 2 benchmarks • 3 datasets

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Most implemented papers

Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture

yhlleo/DeepSegmentor ICCV 2015

In this paper we address three different computer vision tasks using a single basic architecture: depth prediction, surface normal estimation, and semantic labeling.

Maintaining Natural Image Statistics with the Contextual Loss

roimehrez/contextualLoss 13 Mar 2018

Maintaining natural image statistics is a crucial factor in restoration and generation of realistic looking images.

Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres

leoshine/Spherical_Regression CVPR 2019

We observe many continuous output problems in computer vision are naturally contained in closed geometrical manifolds, like the Euler angles in viewpoint estimation or the normals in surface normal estimation.

Deep Iterative Surface Normal Estimation

nnaisense/deep-iterative-surface-normal-estimation CVPR 2020

This results in a state-of-the-art surface normal estimator that is robust to noise, outliers and point density variation, preserves sharp features through anisotropic kernels and equivariance through a local quaternion-based spatial transformer.

Scaling and Benchmarking Self-Supervised Visual Representation Learning

facebookresearch/fair_self_supervision_benchmark ICCV 2019

Self-supervised learning aims to learn representations from the data itself without explicit manual supervision.

GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation

xjqi/GeoNet 13 Dec 2020

Note that GeoNet++ is generic and can be used in other depth/normal prediction frameworks to improve the quality of 3D reconstruction and pixel-wise accuracy of depth and surface normals.

PixelNet: Representation of the pixels, by the pixels, and for the pixels

bdecost/pixelnet 21 Feb 2017

We explore design principles for general pixel-level prediction problems, from low-level edge detection to mid-level surface normal estimation to high-level semantic segmentation.

Generic 3D Representation via Pose Estimation and Matching

amir32002/3D_Street_View 23 Oct 2017

Though a large body of computer vision research has investigated developing generic semantic representations, efforts towards developing a similar representation for 3D has been limited.

Pixel-wise Attentional Gating for Parsimonious Pixel Labeling

aimerykong/Pixel-Attentional-Gating 3 May 2018

To achieve parsimonious inference in per-pixel labeling tasks with a limited computational budget, we propose a \emph{Pixel-wise Attentional Gating} unit (\emph{PAG}) that learns to selectively process a subset of spatial locations at each layer of a deep convolutional network.

GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation

xjqi/GeoNet CVPR 2018

In this paper, we propose Geometric Neural Network (GeoNet) to jointly predict depth and surface normal maps from a single image.