3D Shape Reconstruction
58 papers with code • 2 benchmarks • 8 datasets
Pix3D
Hypersim
ApolloCar3D
4DFAB
HUMAN4D
FewSOL
Foot3D
3D-POP
Latest papers
Benchmarking Encoder-Decoder Architectures for Biplanar X-ray to 3D Shape Reconstruction
naamiinepal/xrayto3d-benchmark
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Our results show that attention-based methods that capture global spatial relationships tend to perform better across all anatomies and datasets; performance on clinically relevant subgroups may be overestimated without disaggregated reporting; ribs are substantially more difficult to reconstruct compared to femur, hip and spine; and the dice score improvement does not always bring a corresponding improvement in the automatic estimation of clinically relevant parameters.
Neural Poisson Surface Reconstruction: Resolution-Agnostic Shape Reconstruction from Point Clouds
Overall, the neural Poisson surface reconstruction not only improves upon the limitations of classical deep neural networks in shape reconstruction but also achieves superior results in terms of reconstruction quality, running time, and resolution agnosticism.
Mesh Density Adaptation for Template-based Shape Reconstruction
ycjungsubhuman/density-adaptation
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In 3D shape reconstruction based on template mesh deformation, a regularization, such as smoothness energy, is employed to guide the reconstruction into a desirable direction.
SwIPE: Efficient and Robust Medical Image Segmentation with Implicit Patch Embeddings
charzharr/miccai23-swipe-implicit-segmentation
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Modern medical image segmentation methods primarily use discrete representations in the form of rasterized masks to learn features and generate predictions.
Real-time Simultaneous Multi-Object 3D Shape Reconstruction, 6DoF Pose Estimation and Dense Grasp Prediction
In this paper, we present a novel method to provide this geometric and semantic information of all objects in the scene as well as feasible grasps on those objects simultaneously.
Parcel3D: Shape Reconstruction from Single RGB Images for Applications in Transportation Logistics
We work towards detecting mishandling of parcels by presenting a novel architecture called CubeRefine R-CNN, which combines estimating a 3D bounding box with an iterative mesh refinement.
Multi-View Azimuth Stereo via Tangent Space Consistency
We present a method for 3D reconstruction only using calibrated multi-view surface azimuth maps.
NAISR: A 3D Neural Additive Model for Interpretable Shape Representation
uncbiag/naisr
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However, given a set of 3D shapes with associated covariates there is at present no shape representation method which allows to precisely represent the shapes while capturing the individual dependencies on each covariate.
Neural Fourier Filter Bank
We present a novel method to provide efficient and highly detailed reconstructions.
OReX: Object Reconstruction from Planar Cross-sections Using Neural Fields
A modest neural network is trained on the input planes to return an inside/outside estimate for a given 3D coordinate, yielding a powerful prior that induces smoothness and self-similarities.
