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3D Reconstruction

55 papers with code · Computer Vision
Subtask of 3D

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Greatest papers with code

Learning to Generate and Reconstruct 3D Meshes with only 2D Supervision

24 Jul 2018pmh47/dirt

Importantly, it can be trained purely from 2D images, without ground-truth pose annotations, and with a single view per instance.

3D RECONSTRUCTION

D2-Net: A Trainable CNN for Joint Description and Detection of Local Features

CVPR 2019 mihaidusmanu/d2-net

In this work we address the problem of finding reliable pixel-level correspondences under difficult imaging conditions.

3D RECONSTRUCTION

D2-Net: A Trainable CNN for Joint Detection and Description of Local Features

9 May 2019mihaidusmanu/d2-net

In this work we address the problem of finding reliable pixel-level correspondences under difficult imaging conditions.

3D RECONSTRUCTION

Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding

CVPR 2019 svip-lab/PlanarReconstruction

In the first stage, we train a CNN to map each pixel to an embedding space where pixels from the same plane instance have similar embeddings.

3D PLANE DETECTION 3D RECONSTRUCTION INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

LabelFusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes

15 Jul 2017RobotLocomotion/LabelFusion

We use an RGBD camera to collect video of a scene from multiple viewpoints and leverage existing reconstruction techniques to produce a 3D dense reconstruction.

3D RECONSTRUCTION POSE ESTIMATION SEMANTIC SEGMENTATION

GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints

ECCV 2018 lzx551402/geodesc

Learned local descriptors based on Convolutional Neural Networks (CNNs) have achieved significant improvements on patch-based benchmarks, whereas not having demonstrated strong generalization ability on recent benchmarks of image-based 3D reconstruction.

3D RECONSTRUCTION

Im2Avatar: Colorful 3D Reconstruction from a Single Image

17 Apr 2018syb7573330/im2avatar

In this work, we study a new problem, that is, simultaneously recovering 3D shape and surface color from a single image, namely "colorful 3D reconstruction".

3D RECONSTRUCTION

Scan2CAD: Learning CAD Model Alignment in RGB-D Scans

CVPR 2019 skanti/Scan2CAD

For a 3D reconstruction of an indoor scene, our method takes as input a set of CAD models, and predicts a 9DoF pose that aligns each model to the underlying scan geometry.

3D RECONSTRUCTION