3D Shape Modeling
11 papers with code • 2 benchmarks • 3 datasets
Image: Gkioxari et al
Benchmarks
These leaderboards are used to track progress in 3D Shape Modeling
| Trend | Dataset | Best Model | Paper | Code | Compare |
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Pix3D
SynFoot
DrivAerNet
Latest papers with no code
Sine Activated Low-Rank Matrices for Parameter Efficient Learning
Low-rank decomposition has emerged as a vital tool for enhancing parameter efficiency in neural network architectures, gaining traction across diverse applications in machine learning.
NeuSDFusion: A Spatial-Aware Generative Model for 3D Shape Completion, Reconstruction, and Generation
3D shape generation aims to produce innovative 3D content adhering to specific conditions and constraints.
ArcGAN: Generative Adversarial Networks for 3D Architectural Image Generation
Due to advancements in infrastructural modulations, architectural design is one of the most peculiar and tedious processes.
TUVF: Learning Generalizable Texture UV Radiance Fields
This allows the texture to be disentangled from the underlying shape and transferable to other shapes that share the same UV space, i. e., from the same category.
Attention-based Part Assembly for 3D Volumetric Shape Modeling
Modeling a 3D volumetric shape as an assembly of decomposed shape parts is much more challenging, but semantically more valuable than direct reconstruction from a full shape representation.
A Temporal Learning Approach to Inpainting Endoscopic Specularities and Its effect on Image Correspondence
In this paper, we aim at removing specular highlights from endoscopic videos using machine learning.
Physically-Aware Generative Network for 3D Shape Modeling
In particular, we introduce a loss and a learning framework that promote two key characteristics of the generated shapes: their connectivity and physical stability.
Deep Optimized Priors for 3D Shape Modeling and Reconstruction
Many learning-based approaches have difficulty scaling to unseen data, as the generality of its learned prior is limited to the scale and variations of the training samples.
Composite Shape Modeling via Latent Space Factorization
We present a novel neural network architecture, termed Decomposer-Composer, for semantic structure-aware 3D shape modeling.
Are Cars Just 3D Boxes? - Jointly Estimating the 3D Shape of Multiple Objects
Current systems for scene understanding typically represent objects as 2D or 3D bounding boxes.
