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Surface Normals Estimation

6 papers with code · Computer Vision

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BlenderProc

25 Oct 2019DLR-RM/BlenderProc

BlenderProc is a modular procedural pipeline, which helps in generating real looking images for the training of convolutional neural networks.

3D OBJECT RECOGNITION DEPTH IMAGE ESTIMATION POSE ESTIMATION SEMANTIC SEGMENTATION SURFACE NORMALS ESTIMATION

Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations

13 Sep 2018DrSleep/multi-task-refinenet

Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards.

MONOCULAR DEPTH ESTIMATION REAL-TIME SEMANTIC SEGMENTATION SURFACE NORMALS ESTIMATION

ClearGrasp: 3D Shape Estimation of Transparent Objects for Manipulation

6 Oct 2019Shreeyak/cleargrasp

To address these challenges, we present ClearGrasp -- a deep learning approach for estimating accurate 3D geometry of transparent objects from a single RGB-D image for robotic manipulation.

DEPTH COMPLETION MONOCULAR DEPTH ESTIMATION SURFACE NORMALS ESTIMATION TRANSPARENT OBJECT DEPTH ESTIMATION TRANSPARENT OBJECT DETECTION

Robust Learning Through Cross-Task Consistency

7 Jun 2020EPFL-VILAB/XTConsistency

Visual perception entails solving a wide set of tasks, e. g., object detection, depth estimation, etc.

3D RECONSTRUCTION DEPTH ESTIMATION MULTI-TASK LEARNING OBJECT DETECTION SURFACE NORMALS ESTIMATION

$360^o$ Surface Regression with a Hyper-Sphere Loss

16 Sep 2019VCL3D/SphericalViewSynthesis

We present a dataset of $360^o$ images of indoor spaces with their corresponding ground truth surface normal, and train a deep convolutional neural network (CNN) on the task of monocular 360 surface estimation.

SURFACE NORMALS ESTIMATION