Hyperbolic Image Segmentation, CVPR 2022

Related tags

Deep Learning segmentation image-segmentation semantic-segmentation hyperbolic-space hyperbolic-embeddings cvpr2022
Overview

Hyperbolic Image Segmentation, CVPR 2022

This is the implementation of paper Hyperbolic Image Segmentation (CVPR 2022).

Figure 1

Repository structure

  • assets : images and stuff
  • datasets : contains integer to class dictionaries, and JSON files that contain the hierarchies used.
  • hesp : the actual code containing layers, models, losses, etc.
  • samples : helper files, bash scripts, and train.py

Code is not complete yet.

How to use the code?

For installation, first run pip install -e . to register the package.

Then, run sh requirements.sh to install the requirements.

The code needs Tensorflow 1, the experiments are performed using Tensorflow 1.14. The tensorflow installed by the script is tensorflow-cpu. Change the commands to install tensorflow on GPU.

To train a model, use this code in samples directory.

python train.py --mode segmenter --batch_size 5 --dataset coco --geometry hyperbolic --dim 256 --c 0.1 --freeze_bn --train --test --backbone_init Path_to_resnet/resnet_v2_101_2017_04_14/resnet_v2_101.ckpt --output_stride 16 --segmenter_ident check

The code will train and test a hyperbolic model using coco stuff dataset, with batch size 5, curvature 0.1, freeze batch normalization, output stride 16. The result will be saved in a folder named poincare-hesp/save/segmenter/hierarchical_coco_d256_hyperbolic_c0.1_os16_resnet_v2_101_bs5_lr0.001_fbnTrue_fbbFalse_check in the samples directory.

Citation

Please consider citing this work using this BibTex entry,

@article{ghadimiatigh2022hyperbolic,
  title={Hyperbolic Image Segmentation},
  author={GhadimiAtigh, Mina and Schoep, Julian and Acar, Erman and van Noord, Nanne and Mettes, Pascal},
  journal={arXiv preprint arXiv:2203.05898},
  year={2022}
}
You might also like...
Stratified Transformer for 3D Point Cloud Segmentation (CVPR 2022)
Stratified Transformer for 3D Point Cloud Segmentation (CVPR 2022)

Stratified Transformer for 3D Point Cloud Segmentation Xin Lai*, Jianhui Liu*, Li Jiang, Liwei Wang, Hengshuang Zhao, Shu Liu, Xiaojuan Qi, Jiaya Jia

DV Lab 195 Jan 1, 2023
Temporally Efficient Vision Transformer for Video Instance Segmentation, CVPR 2022, Oral
Temporally Efficient Vision Transformer for Video Instance Segmentation, CVPR 2022, Oral

Temporally Efficient Vision Transformer for Video Instance Segmentation Temporally Efficient Vision Transformer for Video Instance Segmentation (CVPR

Hust Visual Learning Team 203 Dec 31, 2022
A variational Bayesian method for similarity learning in non-rigid image registration (CVPR 2022)
A variational Bayesian method for similarity learning in non-rigid image registration (CVPR 2022)

A variational Bayesian method for similarity learning in non-rigid image registration We provide the source code and the trained models used in the re

daniel grzech 14 Nov 21, 2022
Sound-guided Semantic Image Manipulation - Official Pytorch Code (CVPR 2022)
Sound-guided Semantic Image Manipulation - Official Pytorch Code (CVPR 2022)

🔉 Sound-guided Semantic Image Manipulation (CVPR2022) Official Pytorch Implementation Sound-guided Semantic Image Manipulation IEEE/CVF Conference on

CVLAB 58 Dec 28, 2022
Official PyTorch implementation of the paper
Official PyTorch implementation of the paper "Deep Constrained Least Squares for Blind Image Super-Resolution", CVPR 2022.

Deep Constrained Least Squares for Blind Image Super-Resolution [Paper] This is the official implementation of 'Deep Constrained Least Squares for Bli

MEGVII Research 141 Dec 30, 2022
Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022
Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022

LDL Paper | Supplementary Material Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution Jie Liang*, Hu

null 150 Dec 26, 2022
Official implementation for
Official implementation for "Style Transformer for Image Inversion and Editing" (CVPR 2022)

Style Transformer for Image Inversion and Editing (CVPR2022) https://arxiv.org/abs/2203.07932 Existing GAN inversion methods fail to provide latent co

Xueqi Hu 153 Dec 2, 2022
Pop-Out Motion: 3D-Aware Image Deformation via Learning the Shape Laplacian (CVPR 2022)
Pop-Out Motion: 3D-Aware Image Deformation via Learning the Shape Laplacian (CVPR 2022)

Pop-Out Motion Pop-Out Motion: 3D-Aware Image Deformation via Learning the Shape Laplacian (CVPR 2022) Jihyun Lee*, Minhyuk Sung*, Hyunjin Kim, Tae-Ky

Jihyun Lee 88 Nov 22, 2022
[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space
[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space by Quande Liu, Cheng Chen, Ji

Quande Liu 178 Jan 6, 2023
Comments
  • '. record' file not found

    '. record' file not found

    Hi! Thanks for sharing the code! I tried to reproduce this work but had some trouble finding 'coco_train.record' and 'coco_val.record'. Will these files be shared? Or shall I download them from elsewhere? Thank you!

    opened by 17762516420 1
  • Code for plotting the gyroplanes

    Code for plotting the gyroplanes

    Hi - Thank you for the great piece of work!

    I was wondering if you were planning on posting the code used for plotting the classes gyroplane on the Poincare ball (i.e. Fig. 1) ? I tried to find more information in the supplementary material as for how these were plotted but in vain.

    Thank you! Darius

    opened by darius522 1
Owner
Mina Ghadimi Atigh
Ph.D. student at the University of Amsterdam
Mina Ghadimi Atigh
GitHub https://minaghadimi.github.io/papers/HIS/index.html
Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed. KDD 2019.

gHHC Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, D

Nicholas Monath 35 Nov 16, 2022
HyperLib: Deep learning in the Hyperbolic space

HyperLib: Deep learning in the Hyperbolic space Background This library implements common Neural Network components in the hypberbolic space (using th

null 105 Dec 25, 2022
PyTorch implementation HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections

HoroPCA This code is the official PyTorch implementation of the ICML 2021 paper: HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projec

HazyResearch 52 Nov 14, 2022
A Python framework for developing parallelized Computational Fluid Dynamics software to solve the hyperbolic 2D Euler equations on distributed, multi-block structured grids.

pyHype: Computational Fluid Dynamics in Python pyHype is a Python framework for developing parallelized Computational Fluid Dynamics software to solve

Mohamed Khalil 21 Nov 22, 2022
The 7th edition of NTIRE: New Trends in Image Restoration and Enhancement workshop will be held on June 2022 in conjunction with CVPR 2022.

NTIRE 2022 - Image Inpainting Challenge Important dates 2022.02.01: Release of train data (input and output images) and validation data (only input) 2

Andrés Romero 37 Nov 27, 2022
Imposter-detector-2022 - HackED 2022 Team 3IQ - 2022 Imposter Detector

HackED 2022 Team 3IQ - 2022 Imposter Detector By Aneeljyot Alagh, Curtis Kan, Jo

Joshua Ji 3 Aug 20, 2022
[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels

Using Unreliable Pseudo Labels Official PyTorch implementation of Semi-Supervised Semantic Segmentation Using Unreliable Pseudo Labels, CVPR 2022. Ple

Haochen Wang 268 Dec 24, 2022
Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic Segmentation (CVPR 2022)

CCAM (Unsupervised) Code repository for our paper "CCAM: Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localizati

Computer Vision Insitute, SZU 113 Dec 27, 2022
FreeSOLO for unsupervised instance segmentation, CVPR 2022

FreeSOLO: Learning to Segment Objects without Annotations This project hosts the code for implementing the FreeSOLO algorithm for unsupervised instanc

NVIDIA Research Projects 253 Jan 2, 2023
Scribble-Supervised LiDAR Semantic Segmentation, CVPR 2022 (ORAL)

Scribble-Supervised LiDAR Semantic Segmentation Dataset and code release for the paper Scribble-Supervised LiDAR Semantic Segmentation, CVPR 2022 (ORA

null 102 Dec 25, 2022