3D Object Reconstruction
56 papers with code • 3 benchmarks • 6 datasets
Image: Choy et al
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Latest papers
TripoSR: Fast 3D Object Reconstruction from a Single Image
This technical report introduces TripoSR, a 3D reconstruction model leveraging transformer architecture for fast feed-forward 3D generation, producing 3D mesh from a single image in under 0. 5 seconds.
FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything
Therefore, this paper introduces FusionVision, an exhaustive pipeline adapted for the robust 3D segmentation of objects in RGB-D imagery.
iFusion: Inverting Diffusion for Pose-Free Reconstruction from Sparse Views
Our strategy unfolds in three steps: (1) We invert the diffusion model for camera pose estimation instead of synthesizing novel views.
Splatter Image: Ultra-Fast Single-View 3D Reconstruction
We introduce the Splatter Image, an ultra-fast approach for monocular 3D object reconstruction which operates at 38 FPS.
Long-Range Grouping Transformer for Multi-View 3D Reconstruction
The tokens in each group are sampled from all views and can provide macro representation for the resided view.
A One Stop 3D Target Reconstruction and multilevel Segmentation Method
We extend object tracking and 3D reconstruction algorithms to support continuous segmentation labels to leverage the advances in the 2D image segmentation, especially the Segment-Anything Model (SAM) which uses the pretrained neural network without additional training for new scenes, for 3D object segmentation.
NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF
Second, our Repulsive UDF is a novel alternative to the occupancy field used in MCC, significantly improving the quality of 3D object reconstruction.
CAD-Estate: Large-scale CAD Model Annotation in RGB Videos
We propose a method for annotating videos of complex multi-object scenes with a globally-consistent 3D representation of the objects.
MobileBrick: Building LEGO for 3D Reconstruction on Mobile Devices
The distinct data modality offered by high-resolution RGB images and low-resolution depth maps captured on a mobile device, when combined with precise 3D geometry annotations, presents a unique opportunity for future research on high-fidelity 3D reconstruction.
UMIFormer: Mining the Correlations between Similar Tokens for Multi-View 3D Reconstruction
We empirically demonstrate on ShapeNet and confirm that our decoupled learning method is adaptable for unstructured multiple images.