human-analysis/neural-architecture-transfer

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human-analysis/neural-architecture-transfer

human-analysis

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Neural Architecture Transfer (Arxiv'20), PyTorch Implementation

Neural Architecture Transfer

Code accompanying the paper.

Neural Architecture Transfer

Zhichao Lu, Gautam Sreekumar, Erik Goodman, Wolfgang Banzhaf, Kalyanmoy Deb, and Vishnu Boddeti

arXiv:2005.05859

Requirements

Python >= 3.7.x, PyTorch >= 1.4.0, timm >= 0.1.18

ImageNet Classification

python evaluator.py --data /path/to/dataset --model subnets/imagenet/NAT-{M1,M2,M3,M4}/net.config

Architecture Transfer

python evaluator.py \
  --data /path/to/dataset \
  --dataset {aircraft,cars,cifar10,cifar100,cinic10,dtd,flowers102,food101,pets,stl10} \
  --model subnets/{dataset}/net-img@{xxx}-flops@{xxx}-top1@{xx.x}/net.config

Scalability to Objectives

Tri-Objective

12-Objective

Architecture Visualization

Acknowledgement

Codes are modified from OnceForAll and pytorch-image-models

MUXConv

MUXConv: Information Multiplexing in Convolutional Neural Networks (CVPR '20), Pytorch Implementation

pytorchnet

Generalized Framework for PyTorch

secure-face-matching

MaxEnt-ARL

PyTorch Implementation of CVPR'19 (oral) - Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach

intrinsic-dimensionality

PyTorch Implementation of CVPR'19 - On the Intrinsic Dimensionality of Image Representation

causal-relations-between-representations

diverse3dface

RankGAN

RankGAN: A Maximum Margin Ranking GAN for Generating Faces

LBCNN

Local Binary Convolutional Neural Networks

3dfacefill

Repository for 3DFaceFill: An Analysis-by-Synthesis Approach for Face Completion

hers-encrypted-image-search

HERS: Homomorphically Encrypted Representation Search

encrypted-biometric-fusion

kernel-adversarial-representation-learning

On the Global Optima of Kernelized Adversarial Representation Learning (ICCV'19), PyTorch Implementation

nsganetv1

neural-structural-identification

capacity-generative-face-models

Repository for the paper titled "On the Biometric Capacity of Generative Face Models"

Jupyter Notebook

tensorflownet

moea-nas-framework