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
Latest papers with no code
Towards 3D Vision with Low-Cost Single-Photon Cameras
We present a method for reconstructing 3D shape of arbitrary Lambertian objects based on measurements by miniature, energy-efficient, low-cost single-photon cameras.
UPNeRF: A Unified Framework for Monocular 3D Object Reconstruction and Pose Estimation
Monocular 3D reconstruction for categorical objects heavily relies on accurately perceiving each object's pose.
MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction
MVDiffusion++ achieves superior flexibility and scalability with two surprisingly simple ideas: 1) A ``pose-free architecture'' where standard self-attention among 2D latent features learns 3D consistency across an arbitrary number of conditional and generation views without explicitly using camera pose information; and 2) A ``view dropout strategy'' that discards a substantial number of output views during training, which reduces the training-time memory footprint and enables dense and high-resolution view synthesis at test time.
2L3: Lifting Imperfect Generated 2D Images into Accurate 3D
Specifically, we first leverage to decouple the shading information from the generated images to reduce the impact of inconsistent lighting; then, we introduce mono prior with view-dependent transient encoding to enhance the reconstructed normal; and finally, we design a view augmentation fusion strategy that minimizes pixel-level loss in generated sparse views and semantic loss in augmented random views, resulting in view-consistent geometry and detailed textures.
In-Hand 3D Object Reconstruction from a Monocular RGB Video
We evaluate our approach on HO3D and HOD datasets and demonstrate that it outperforms the state-of-the-art methods in terms of reconstruction surface quality, with an improvement of $52\%$ on HO3D and $20\%$ on HOD.
DreamComposer: Controllable 3D Object Generation via Multi-View Conditions
However, due to the lack of information from multiple views, these works encounter difficulties in generating controllable novel views.
3DFusion, A real-time 3D object reconstruction pipeline based on streamed instance segmented data
To achieve real-time performance, the paper proposes a method that effectively samples consecutive frames to reduce network load while ensuring reconstruction quality.
Single-view 3D Scene Reconstruction with High-fidelity Shape and Texture
Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, overlooking object appearances and fine shape details.
Effect of structure-based training on 3D localization precision and quality
This study introduces a structural-based training approach for CNN-based algorithms in single-molecule localization microscopy (SMLM) and 3D object reconstruction.
SimNP: Learning Self-Similarity Priors Between Neural Points
(1) We design the first neural point representation on a category level by utilizing the concept of coherent point clouds.
