vislearn/conditional_INNs

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Python
Created almost 5 years ago
Updated about 4 years ago

vislearn/conditional_INNs

vislearn

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Code for the paper "Guided Image Generation with Conditional Invertible Neural Networks" (2019)

FrEIA

Framework for Easily Invertible Architectures

ControlNet-XS

ngransac

Neural-Guided RANSAC for Estimating Epipolar Geometry from Sparse Correspondences

LessMore

Learning Less is More - 6D Camera Localization via 3D Surface Regression

dsacstar

DSAC* for Visual Camera Re-Localization (RGB or RGB-D)

DSACLine

Differentiable RANSAC: Learning Robust Line Fitting

analyzing_inverse_problems

Code for the paper "Analyzing inverse problems with invertible neural networks." (2018)

Jupyter Notebook

esac

ESAC - Expert Sample Consensus Applied To Camera Re-Localization

ngdsac_camreloc

Neural-Guided, Differentiable RANSAC for Camera Re-Localization (NG-DSAC++)

IB-INN

Code for the paper "Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification" (2020)

FFF

Free-form flows are a generative model training a pair of neural networks via maximum likelihood

Jupyter Notebook

ngdsac_horizon

Neural-Guided, Differentiable RANSAC for Horizon Line Estimation

GIN

Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)

HINT

Code for the research paper "HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference".

trustworthy_GCs

Materials for the paper https://arxiv.org/pdf/2007.15036.pdf

3dcv-students

Exercises for the lecture "Computer Vision: 3D Reconstruction"

Jupyter Notebook

inn_toy_data

Code for artificial toy data sets used to evaluate (conditional) invertible neural networks and related methods

Coupling-Universality

Jupyter Notebook

ML-Tutorial

Introduction to Machine Learning using scikit-learn and PyTorch

Jupyter Notebook

gmbench

Code for “A Comparative Study of Graph Matching Algorithms in Computer Vison” (ECCV 2022)

MLAE

Maximum Likelihood Training of Autoencoders

Jupyter Notebook

libct

A fast approximate primal-dual solver for tracking-by-assignment cell-tracking problems

libmpopt

Library for Message Passing Optimization Techniques

combilp

Exact MAP-Inference by Confining Combinatorial Search with LP Relaxation

Gaussianization-Bound

Code to paper "On the Convergence Rate of Gaussianization with Random Rotations"