3D Architecture
11 papers with code • 0 benchmarks • 0 datasets
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Use these libraries to find 3D Architecture models and implementationsMost implemented papers
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Detection
Efforts to automate the reconstruction of neural circuits from 3D electron microscopic (EM) brain images are critical for the field of connectomics.
Deep Learning Convolutional Networks for Multiphoton Microscopy Vasculature Segmentation
Recently there has been an increasing trend to use deep learning frameworks for both 2D consumer images and for 3D medical images.
3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation
We present 3DMV, a novel method for 3D semantic scene segmentation of RGB-D scans in indoor environments using a joint 3D-multi-view prediction network.
DR-Unet104 for Multimodal MRI brain tumor segmentation
We verified the effect of introducing the regularisation of dropout with small rate (e. g. 0. 2) on the architecture, and found a dropout of 0. 2 improved the overall performance compared to no dropout, or a dropout of 0. 5.
Diverse Temporal Aggregation and Depthwise Spatiotemporal Factorization for Efficient Video Classification
By using the proposed temporal modeling method (T-OSA), and the efficient factorized component (D(2+1)D), we construct two types of VoV3D networks, VoV3D-M and VoV3D-L.
ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D Understanding
Then, ULIP learns a 3D representation space aligned with the common image-text space, using a small number of automatically synthesized triplets.
Improved distinct bone segmentation in upper-body CT through multi-resolution networks
The approach thus improves the accuracy and efficiency of distinct bone segmentation from upper-body CT.
PAniC-3D: Stylized Single-view 3D Reconstruction from Portraits of Anime Characters
We propose PAniC-3D, a system to reconstruct stylized 3D character heads directly from illustrated (p)ortraits of (ani)me (c)haracters.
SkateboardAI: The Coolest Video Action Recognition for Skateboarding
Impressed by the coolest skateboarding sports program from 2021 Tokyo Olympic Games, we are the first to curate the original real-world video datasets "SkateboardAI" in the wild, even self-design and implement diverse uni-modal and multi-modal video action recognition approaches to recognize different tricks accurately.
SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images
In this paper, we introduce SAM-Med3D for general-purpose segmentation on volumetric medical images.