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Projects in Awesome Lists tagged with implicit-representions

A curated list of projects in awesome lists tagged with implicit-representions .

https://github.com/autonomousvision/differentiable_volumetric_rendering

This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"

3d-deep-learning 3d-reconstruction cvpr-2020 cvpr2020 differentiable-rendering dvr implicit-representions mesh-generation novel-view-synthesis

Last synced: 04 Apr 2025

https://github.com/ShivamDuggal4/TARS3D

Topologically-Aware Deformation Fields for Single-View 3D Reconstruction (CVPR 2022)

3d-reconstruction correspondences cvpr2022 deformations implicit-representions neural-fields single-view-reconstruction topology

Last synced: 08 May 2025

https://github.com/Wuziyi616/IF-Defense

This is the official pytorch implementation for paper: IF-Defense: 3D Adversarial Point Cloud Defense via Implicit Function based Restoration

3d-attack 3d-reconstruction adversarial-machine-learning deep-learning defense dgcnn implicit-representions point-cloud pointconv pointnet pointnet2 pytorch rs-cnn

Last synced: 21 Nov 2025

https://github.com/juliageometry/descartes.jl

Software Defined Solid Modeling

cad implicit-representions solid-modeling

Last synced: 19 Apr 2025

https://github.com/jloveric/high-order-layers-torch

High order and sparse layers in pytorch. Lagrange Polynomial, Piecewise Lagrange Polynomial, Piecewise Discontinuous Lagrange Polynomial (Chebyshev nodes) and Fourier Series layers of arbitrary order. Piecewise implementations could be thought of as a 1d grid (for each neuron) where each grid element is Lagrange polynomial. Both full connected and convolutional layers included.

chebyshev-polynomials deeplearning discontinuous fluid-dynamics fourier-series grid high-order-methods hp-refinement implicit-representions lagrange-polynomial-interpolation piecewise-polynomial pytorch pytorch-lightning sparse-network spline

Last synced: 21 Aug 2025

https://github.com/yannick-kees/shape-space-learning

Implementation of two phase field approaches for the surface reconstruction problem and shape space learning. One based of the Modica-Mortola theorem and the other based on Ambrosio-Tortorelli

ambrosio-tortorelli deep-learning implicit-neural-representation implicit-representions modica-mortola pytorch shape-space surface-reconstruction

Last synced: 19 May 2026