GitHub topics: implicit-representions
autonomousvision/convolutional_occupancy_networks
[ECCV'20] Convolutional Occupancy Networks
Language: Python - Size: 10.5 MB - Last synced at: 14 days ago - Pushed at: almost 2 years ago - Stars: 869 - Forks: 120

zubair-irshad/shapo
Pytorch code for ECCV'22 paper. ShAPO: Implicit Representations for Multi-Object Shape, Appearance and Pose Optimization
Language: Python - Size: 36.8 MB - Last synced at: 29 days ago - Pushed at: 11 months ago - Stars: 189 - Forks: 11

autonomousvision/differentiable_volumetric_rendering
This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"
Language: Python - Size: 22.1 MB - Last synced at: 14 days ago - Pushed at: over 3 years ago - Stars: 818 - Forks: 92

JuliaGeometry/Descartes.jl
Software Defined Solid Modeling
Language: Julia - Size: 332 KB - Last synced at: 3 days ago - Pushed at: 11 months ago - Stars: 48 - Forks: 2

subeeshvasu/Awsome_Deep_Geometry_Learning
A list of resources about deep learning solutions on 3D shape processing
Size: 1.5 MB - Last synced at: about 2 months ago - Pushed at: almost 4 years ago - Stars: 348 - Forks: 57

jloveric/high-order-implicit-representation
Implicit representation of various things using PyTorch and high order layers
Language: Python - Size: 5.08 MB - Last synced at: 2 months ago - Pushed at: about 1 year ago - Stars: 8 - Forks: 2

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.
Language: Python - Size: 5.51 MB - Last synced at: about 1 month ago - Pushed at: 12 months ago - Stars: 44 - Forks: 4

POSTECH-CVLab/SCNeRF
[ICCV21] Self-Calibrating Neural Radiance Fields
Language: Python - Size: 21.8 MB - Last synced at: 13 days ago - Pushed at: almost 3 years ago - Stars: 469 - Forks: 45

ShivamDuggal4/TARS3D
Topologically-Aware Deformation Fields for Single-View 3D Reconstruction (CVPR 2022)
Language: Python - Size: 2.32 MB - Last synced at: 29 days ago - Pushed at: almost 3 years ago - Stars: 88 - Forks: 6

pablopalafox/npms
Official implementation of NPMs: Neural Parametric Models for 3D Deformable Shapes - ICCV 2021
Language: Python - Size: 9.6 MB - Last synced at: 6 months ago - Pushed at: about 2 years ago - Stars: 126 - Forks: 15

ychen921/Implicit-Neural-Representation
Simple implementation and improvement of INRs
Language: Jupyter Notebook - Size: 31.5 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

benjaminocampo/ISHate
This repository contains the dataset and implementation details of the paper "An In-depth Analysis of Implicit and Subtle Hate Speech Messages" accepted at EACL 2023.
Language: Python - Size: 9.11 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 6 - Forks: 2

Wuziyi616/IF-Defense
This is the official pytorch implementation for paper: IF-Defense: 3D Adversarial Point Cloud Defense via Implicit Function based Restoration
Language: Python - Size: 5.97 MB - Last synced at: about 1 year ago - Pushed at: almost 4 years ago - Stars: 59 - Forks: 11

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
Language: Python - Size: 340 MB - Last synced at: 3 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

basilevh/occlusions-4d
Revealing Occlusions with 4D Neural Fields (CVPR 2022 Oral) - Official Implementation
Language: Python - Size: 293 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 71 - Forks: 5
