Learning Cortical Anomaly through Masked Encoding for Unsupervised Heterogeneity Mapping.
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Updated
Jun 13, 2024 - Python
Learning Cortical Anomaly through Masked Encoding for Unsupervised Heterogeneity Mapping.
Mixed (structured/unstructured) 3D mesh generator based on curved cuboid elements (primitives)
A minimal, standalone viewer GUI for 3D animations stored as stop-motion sequences of individual .obj mesh files.
Smplify-X implementation. (2024. 03. 18 No Error & Recent version)
Implemented a paper performing loop subdivison and simplification using error quadratic metrics on 3D meshes
Benchmark for visual localization on imperfect 3D mesh models from the Internet
a pyqtgraph GLViewWidget based viewer utility for viewing mesh, adding images, or text to the 3D view.
TEMPEH reconstructs 3D heads in dense semantic correspondence from calibrated multi-view images in about 0.3 seconds.
Official Pytorch implementation of "Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Pose", ECCV 2020
This is a implementation of the 3D FLAME model in PyTorch
A 3d cloud mesh is generated from a, set of photos taken from a drone, in airsim environment.
Tensorflow framework for the FLAME 3D head model. The code demonstrates how to sample 3D heads from the model, fit the model to 2D or 3D keypoints, and how to generate textured head meshes from Images.
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.
MeshRunner - Improved classification of 3D mesh objects
Python module to query an fetch the 3D-ARD project
Description, instructions and supporting code for the ECCV 2020 SHARP Workshop and Challenge (SHApe Recovery from Partial textured 3D scans)
State-of-the-art methods on monocular 3D pose estimation / 3D mesh recovery
A collection of sensor maps collected by Google's Tango Tablet, accompanied with layout maps
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