Object Reconstruction
78 papers with code • 0 benchmarks • 2 datasets
Benchmarks
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Libraries
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A Large Dataset of Object Scans
HOWS
Most implemented papers
CoReNet: Coherent 3D scene reconstruction from a single RGB image
google-research/corenet
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ECCV 2020
Furthermore, we adapt our model to address the harder task of reconstructing multiple objects from a single image.
AlignSDF: Pose-Aligned Signed Distance Fields for Hand-Object Reconstruction
zerchen/AlignSDF
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We show that such aligned SDFs better focus on reconstructing shape details and improve reconstruction accuracy both for hands and objects.
Benchmarks and Challenges in Pose Estimation for Egocentric Hand Interactions with Objects
facebookresearch/assemblyhands-toolkit
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We interact with the world with our hands and see it through our own (egocentric) perspective.
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.
3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversarial Network
We introduce a data-driven approach to aid the repairing and conservation of archaeological objects: ORGAN, an object reconstruction generative adversarial network (GAN).
Learning Free-Form Deformations for 3D Object Reconstruction
Representing 3D shape in deep learning frameworks in an accurate, efficient and compact manner still remains an open challenge.
Deep Single-View 3D Object Reconstruction with Visual Hull Embedding
qweas120/PSVH-3d-reconstruction
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The key idea of our method is to leverage object mask and pose estimation from CNNs to assist the 3D shape learning by constructing a probabilistic single-view visual hull inside of the network.
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
EdwardSmith1884/GEOMetrics
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Mesh models are a promising approach for encoding the structure of 3D objects.
Multi-camera calibration with pattern rigs, including for non-overlapping cameras: CALICO
Infrastructure-based approaches are not suitable for stationary camera systems, and pattern-based approaches may constrain camera placement because shared fields of view or extremely large patterns are required.
