3D Object Reconstruction
61 papers with code • 4 benchmarks • 7 datasets
Image: Choy et al
Benchmarks
These leaderboards are used to track progress in 3D Object Reconstruction
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Libraries
Use these libraries to find 3D Object Reconstruction models and implementationsDatasets
ShapeNet
BEHAVE
X3D
Parcel3D
A collection of 131 CT datasets of pieces of modeling clay containing stones
Corn Seeds Dataset
Most implemented papers
Grasping Field: Learning Implicit Representations for Human Grasps
korrawe/grasping_field_demo
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Specifically, our generative model is able to synthesize high-quality human grasps, given only on a 3D object point cloud.
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision
xcyan/nips16_PTN
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NeurIPS 2016
We demonstrate the ability of the model in generating 3D volume from a single 2D image with three sets of experiments: (1) learning from single-class objects; (2) learning from multi-class objects and (3) testing on novel object classes.
3D Object Reconstruction from a Single Depth View with Adversarial Learning
In this paper, we propose a novel 3D-RecGAN approach, which reconstructs the complete 3D structure of a given object from a single arbitrary depth view using generative adversarial networks.
Dense 3D Object Reconstruction from a Single Depth View
Yang7879/3D-RecGAN-extended
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Unlike existing work which typically requires multiple views of the same object or class labels to recover the full 3D geometry, the proposed 3D-RecGAN++ only takes the voxel grid representation of a depth view of the object as input, and is able to generate the complete 3D occupancy grid with a high resolution of 256^3 by recovering the occluded/missing regions.
3D Point Capsule Networks
yongheng1991/3D-point-capsule-networks
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CVPR 2019
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data.
Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning
ShichenLiu/SoftRas
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ICCV 2019
Rendering bridges the gap between 2D vision and 3D scenes by simulating the physical process of image formation.
Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging
Nevertheless, visual monitoring of fetal motion based on displayed slices, and navigation at the level of stacks-of-slices is inefficient.
UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction
autonomousvision/unisurf
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ICCV 2021
At the same time, neural radiance fields have revolutionized novel view synthesis.
Joint Reconstruction of 3D Human and Object via Contact-Based Refinement Transformer
As a result, our CONTHO achieves state-of-the-art performance in both human-object contact estimation and joint reconstruction of 3D human and object.
Hierarchical Surface Prediction for 3D Object Reconstruction
A major limitation of such approaches is that they only predict a coarse resolution voxel grid, which does not capture the surface of the objects well.
