PyTorch implementation of Octave Convolution with pre-trained Oct-ResNet and Oct-MobileNet models

Overview

octconv.pytorch

PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution

ResNet-50/101 on ImageNet

Architecture LR decay strategy Parameters GFLOPs Top-1 / Top-5 Accuracy (%)
ResNet-50 step (90 epochs) 25.557M 4.089 76.010 / 92.834
ResNet-50 cosine (120 epochs) 25.557M 4.089 77.150 / 93.468
Oct-ResNet-50 (alpha=0.5) cosine (120 epochs) 25.557M 2.367 77.640 / 93.662
ResNet-101 cosine (120 epochs) 44.549M 7.801 78.898 / 94.304
Oct-ResNet-101 (alpha=0.5) cosine (120 epochs) 44.549M 3.991 78.794 / 94.330
ResNet-152 cosine (120 epochs) 60.193M 11.514 79.234 / 94.556
Oct-ResNet-152 (alpha=0.5) cosine (120 epochs) 60.193M 5.615 79.258 / 94.480

MobileNet V1 on ImageNet

Architecture LR decay strategy Parameters FLOPs Top-1 / Top-5 Accuracy (%)
MobileNetV1 cosine (150 epochs) 4.232M 568.7M 72.238 / 90.536
Oct-MobileNetV1 cosine (150 epochs) 4.232M 318.2M 71.254 / 89.728

Acknowledgement

Official MXNet implmentation by @cypw

Citation

@InProceedings{Chen_2019_ICCV,
author = {Chen, Yunpeng and Fan, Haoqi and Xu, Bing and Yan, Zhicheng and Kalantidis, Yannis and Rohrbach, Marcus and Yan, Shuicheng and Feng, Jiashi},
title = {Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks With Octave Convolution},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}
Learning from Synthetic Shadows for Shadow Detection and Removal [Inoue+, IEEE TCSVT 2020].

Learning from Synthetic Shadows for Shadow Detection and Removal (IEEE TCSVT 2020) Overview This repo is for the paper "Learning from Synthetic Shadow

Naoto Inoue 67 Dec 28, 2022
Replication of Pix2Seq with Pretrained Model

Pretrained-Pix2Seq We provide the pre-trained model of Pix2Seq. This version contains new data augmentation. The model is trained for 300 epochs and c

peng gao 51 Nov 22, 2022
MADT: Offline Pre-trained Multi-Agent Decision Transformer

MADT: Offline Pre-trained Multi-Agent Decision Transformer A link to our paper can be found on Arxiv. Overview Official codebase for Offline Pre-train

Linghui Meng 51 Dec 21, 2022
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).

Knowledge Informed Machine Learning using a Weibull-based Loss Function Exploring the concept of knowledge-informed machine learning with the use of a

Tim 43 Dec 14, 2022
Minimal fastai code needed for working with pytorch

fastai_minima A mimal version of fastai with the barebones needed to work with Pytorch #all_slow Install pip install fastai_minima How to use This lib

Zachary Mueller 14 Oct 21, 2022
Code release for The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification (TIP 2020)

The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification Code release for The Devil is in the Channels: Mutual-Channel

PRIS-CV: Computer Vision Group 230 Dec 31, 2022
This is just a funny project that we want to see AutoEncoder (AE) can actually work to enhance the features we want

Funny_muscle_enhancer :) 1.Discription: This is just a funny project that we want to see AutoEncoder (AE) can actually work on the some features. We w

Jing-Yao Chen (Jacob) 8 Oct 01, 2022
FFTNet vocoder implementation

Unofficial Implementation of FFTNet vocode paper. implement the model. implement tests. overfit on a single batch (sanity check). linearize weights fo

Eren Gölge 81 Dec 08, 2022
Convert scikit-learn models to PyTorch modules

sk2torch sk2torch converts scikit-learn models into PyTorch modules that can be tuned with backpropagation and even compiled as TorchScript. Problems

Alex Nichol 101 Dec 16, 2022
Open-World Entity Segmentation

Open-World Entity Segmentation Project Website Lu Qi*, Jason Kuen*, Yi Wang, Jiuxiang Gu, Hengshuang Zhao, Zhe Lin, Philip Torr, Jiaya Jia This projec

DV Lab 410 Jan 03, 2023
Official Pytorch implementation of Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference (ICLR 2022)

The Official Implementation of CLIB (Continual Learning for i-Blurry) Online Continual Learning on Class Incremental Blurry Task Configuration with An

NAVER AI 34 Oct 26, 2022
using yolox+deepsort for object-tracker

YOLOX_deepsort_tracker yolox+deepsort实现目标跟踪 最新的yolox尝尝鲜~~(yolox正处在频繁更新阶段,因此直接链接yolox仓库作为子模块) Install Clone the repository recursively: git clone --rec

245 Dec 26, 2022
Extreme Rotation Estimation using Dense Correlation Volumes

Extreme Rotation Estimation using Dense Correlation Volumes This repository contains a PyTorch implementation of the paper: Extreme Rotation Estimatio

Ruojin Cai 29 Nov 18, 2022
Real-time 3D multi-person detection made easy with OpenPose and the ZED

OpenPose ZED This sample show how to simply use the ZED with OpenPose, the deep learning framework that detects the skeleton from a single 2D image. T

blanktec 5 Nov 06, 2020
Code and real data for the paper "Counterfactual Temporal Point Processes", available at arXiv.

counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code

Networks Learning 11 Dec 09, 2022
Mixed Transformer UNet for Medical Image Segmentation

MT-UNet Update 2021/11/19 Thank you for your interest in our work. We have uploaded the code of our MTUNet to help peers conduct further research on i

dotman 92 Dec 25, 2022
Tensorflow implementation of the paper "HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences", CVPR 2021.

HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences Tensorflow implementation of the paper "HumanGPS: Geodesic PreServing Feature fo

Google Interns 50 Dec 21, 2022
The code for our CVPR paper PISE: Person Image Synthesis and Editing with Decoupled GAN, Project Page, supp.

PISE The code for our CVPR paper PISE: Person Image Synthesis and Editing with Decoupled GAN, Project Page, supp. Requirement conda create -n pise pyt

jinszhang 110 Nov 21, 2022
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱

Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har

labml.ai 1.2k Dec 25, 2022
Emotional conditioned music generation using transformer-based model.

This is the official repository of EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation. The paper has b

hung anna 96 Nov 09, 2022