A Pytorch implementation of "Manifold Matching via Deep Metric Learning for Generative Modeling" (ICCV 2021)

Overview

Manifold Matching via Deep Metric Learning for Generative Modeling

A Pytorch implementation of "Manifold Matching via Deep Metric Learning for Generative Modeling" (ICCV 2021).

Paper: https://arxiv.org/abs/2106.10777

Objective functions

Objective for metric learning:

triplet_loss = triplet_(ml_real_out,ml_real_out_shuffle,ml_fake_out_shuffle)

Objective for manifold matching with learned metric:

g_loss = p_dist + c_dist 

where

ml_real_out = netML(real_img) # real data
ml_fake_out = netML(fake_img) # generated data 

# shuffle in batch
r1=torch.randperm(batch_size)
r2=torch.randperm(batch_size)
ml_real_out_shuffle = ml_real_out[r1[:, None]].view(ml_real_out.shape[0],ml_real_out.shape[-1])
ml_fake_out_shuffle = ml_fake_out[r2[:, None]].view(ml_fake_out.shape[0],ml_fake_out.shape[-1])

# pairwise distances 
pd_r = pairwise_distances(ml_real_out, ml_real_out) 
pd_f = pairwise_distances(ml_fake_out, ml_fake_out)
 
# matching terms 
p_dist =  torch.dist(pd_r,pd_f,2) # matching 2-diameters             
c_dist = torch.dist(ml_real_out.mean(0),ml_fake_out.mean(0),2) # matching centroids  

Dependencies

  • Pytorch 1.0.1

Dataset

Download data to the data path. The sample code uses CelebA dataset.

Training

To train a model for unconditonal generation, run:

python train.py

       

We also tried our objective on generating higher resolution images using a StyleGAN2 data generator and a simple metric generator. Implemenation details can be found here. Below are randomly generated 512x512 samples on FFHQ dataset at ~150K iterations:

Citation

@misc{daiandhang2021manifold,
      title={Manifold Matching via Deep Metric Learning for Generative Modeling}, 
      author={Mengyu Dai and Haibin Hang},
      year={2021},
      eprint={2106.10777},
      archivePrefix={arXiv}
}
Group Activity Recognition with Clustered Spatial Temporal Transformer

GroupFormer Group Activity Recognition with Clustered Spatial-TemporalTransformer Backbone Style Action Acc Activity Acc Config Download Inv3+flow+pos

28 Dec 12, 2022
Code for "Learning Structural Edits via Incremental Tree Transformations" (ICLR'21)

Learning Structural Edits via Incremental Tree Transformations Code for "Learning Structural Edits via Incremental Tree Transformations" (ICLR'21) 1.

NeuLab 40 Dec 23, 2022
Manifold-Mixup implementation for fastai V2

Manifold Mixup Unofficial implementation of ManifoldMixup (Proceedings of ICML 19) for fast.ai (V2) based on Shivam Saboo's pytorch implementation of

Nestor Demeure 16 Jul 25, 2022
A little software to generate and save Julia or Mandelbrot's Fractals.

Julia-Mandelbrot-s-Fractals A little software to generate and save Julia or Mandelbrot's Fractals. Dependencies : Python 3.7 or more. (Also possible t

Olivier 0 Jul 09, 2022
This code is 3d-CNN model that can predict environmental value

Predict-environmental-value-3dCNN This code is 3d-CNN model that can predict environmental value. Firstly, I built a model that can create a lot of bu

1 Jan 06, 2022
Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network

DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the

Qiao Liu 50 Dec 18, 2022
UMPNet: Universal Manipulation Policy Network for Articulated Objects

UMPNet: Universal Manipulation Policy Network for Articulated Objects Zhenjia Xu, Zhanpeng He, Shuran Song Columbia University Robotics and Automation

Columbia Artificial Intelligence and Robotics Lab 33 Dec 03, 2022
wmctrl ported to Python Ctypes

work in progress wmctrl is a command that can be used to interact with an X Window manager that is compatible with the EWMH/NetWM specification. wmctr

Iyad Ahmed 22 Dec 31, 2022
For holding anime-related object classification and detection models

Animesion An end-to-end framework for anime-related object classification, detection, segmentation, and other models. Update: 01/22/2020. Due to time-

Edwin Arkel Rios 72 Nov 30, 2022
Square Root Bundle Adjustment for Large-Scale Reconstruction

RootBA: Square Root Bundle Adjustment Project Page | Paper | Poster | Video | Code Table of Contents Citation Dependencies Installing dependencies on

Nikolaus Demmel 205 Dec 20, 2022
Supplementary code for SIGGRAPH 2021 paper: Discovering Diverse Athletic Jumping Strategies

SIGGRAPH 2021: Discovering Diverse Athletic Jumping Strategies project page paper demo video Prerequisites Important Notes We suspect there are bugs i

54 Dec 06, 2022
Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark

This dataset is a large-scale dataset for moving object detection and tracking in satellite videos, which consists of 40 satellite videos captured by Jilin-1 satellite platforms.

Qingyong 87 Dec 22, 2022
Visualizing Yolov5's layers using GradCam

YOLO-V5 GRADCAM I constantly desired to know to which part of an object the object-detection models pay more attention. So I searched for it, but I di

Pooya Mohammadi Kazaj 200 Jan 01, 2023
A collection of resources on GAN Inversion.

This repo is a collection of resources on GAN inversion, as a supplement for our survey

Learning To Have An Ear For Face Super-Resolution

Learning To Have An Ear For Face Super-Resolution [Project Page] This repository contains demo code of our CVPR2020 paper. Training and evaluation on

50 Nov 16, 2022
GenshinMapAutoMarkTools - Tools To add/delete/refresh resources mark in Genshin Impact Map

使用说明 适配 windows7以上 64位 原神1920x1080窗口(其他分辨率后续适配) 待更新渊下宫 English version is to be

Zero_Circle 209 Dec 28, 2022
WSDM2022 Challenge - Large scale temporal graph link prediction

WSDM 2022 Large-scale Temporal Graph Link Prediction - Baseline and Initial Test Set WSDM Cup Website link Link to this challenge This branch offers A

Deep Graph Library 34 Dec 29, 2022
TorchDistiller - a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.

This project is a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and i

yifan liu 147 Dec 03, 2022
DeLiGAN - This project is an implementation of the Generative Adversarial Network

This project is an implementation of the Generative Adversarial Network proposed in our CVPR 2017 paper - DeLiGAN : Generative Adversarial Net

Video Analytics Lab -- IISc 110 Sep 13, 2022