TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network

Overview

TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network

Created by Seunghoon Hong, Junhyuk Oh, Honglak Lee and Bohyung Han

Project page: [http://cvlab.postech.ac.kr/research/transfernet/]

Introduction

This repository contains the source code for the semantic segmentation algorithm described in the following paper:

  • Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han, "Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network" In IEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
@inproceedings{HongOLH2016,
  title={Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network},
  author={Hong, Seunghoon and Oh, Junhyuk and Lee, Honglak and Han, Bohyung},
  booktitle={Computer Vision and Pattern Recognition (CVPR), 2016 IEEE Conference on},
  year={2016}
}

Pleae refer to our arXiv tech report for details.

Installation

You need to compile the modified Caffe library in this repository. Please consult Caffe installation guide for details. After installing rquired libraries for Caffe, you need to compile both Caffe and its Matlab interface as follows:

cd caffe
make all
make matcaffe

After installing Caffe, you can download datasets, pre-trained models, and other libraries by following script:

setup.sh

Training

Training procedures are composed of two steps, which are implemented in different directories:

  • training/1_train_attention : pre-train attention and classification network with image-level class labels.
  • training/2_train_segmentation : train entire network including a decoder with pixel-wise class labels.

You can run training with following scripts

cd training
./1_train_attention.sh
./2_train_segmentation.sh

Inference

You can run inference on PASCAL VOC 2012 validatoin images using the trained model as follow:

cd inference
matlab -nodesktop -r run_inference

By default, this script will perform an inference on PASCAL VOC 2012 validation images using the pre-trained model. You may need to modify the code if you want to apply the model to different dataset or use the different models.

Licence

This software is for research purpose only. Check LICENSE file for details.

Atif Hassan 103 Dec 14, 2022
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?"

DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re

Guohao Li 612 Nov 15, 2022
Forecasting with Gradient Boosted Time Series Decomposition

ThymeBoost ThymeBoost combines time series decomposition with gradient boosting to provide a flexible mix-and-match time series framework for spicy fo

131 Jan 08, 2023
a general-purpose Transformer based vision backbone

Swin Transformer By Ze Liu*, Yutong Lin*, Yue Cao*, Han Hu*, Yixuan Wei, Zheng Zhang, Stephen Lin and Baining Guo. This repo is the official implement

Microsoft 9.9k Jan 08, 2023
L-Verse: Bidirectional Generation Between Image and Text

Far beyond learning long-range interactions of natural language, transformers are becoming the de-facto standard for many vision tasks with their power and scalabilty

Kim, Taehoon 102 Dec 21, 2022
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)

Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients

Shigang Li 9 Oct 29, 2022
UFT - Universal File Transfer With Python

UFT 2.0.0 UFT (Universal File Transfer) is a CLI tool , which can be used to upl

Merwin 1 Feb 18, 2022
Codes for the compilation and visualization examples to the HIF vegetation dataset

High-impedance vegetation fault dataset This repository contains the codes that compile the "Vegetation Conduction Ignition Test Report" data, which a

1 Dec 12, 2021
Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)

StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery (ICCV 2021 Oral) Run this model on Replicate Optimization: Global directions: Mapper: Check ou

3.3k Jan 05, 2023
RoMA: Robust Model Adaptation for Offline Model-based Optimization

RoMA: Robust Model Adaptation for Offline Model-based Optimization Implementation of RoMA: Robust Model Adaptation for Offline Model-based Optimizatio

9 Oct 31, 2022
Deep learning image registration library for PyTorch

TorchIR: Pytorch Image Registration TorchIR is a image registration library for deep learning image registration (DLIR). I have integrated several ide

Bob de Vos 40 Dec 16, 2022
【CVPR 2021, Variational Inference Framework, PyTorch】 From Rain Generation to Rain Removal

From Rain Generation to Rain Removal (CVPR2021) Hong Wang, Zongsheng Yue, Qi Xie, Qian Zhao, Yefeng Zheng, and Deyu Meng [PDF&&Supplementary Material]

Hong Wang 48 Nov 23, 2022
This is the code of NeurIPS'21 paper "Towards Enabling Meta-Learning from Target Models".

ST This is the code of NeurIPS 2021 paper "Towards Enabling Meta-Learning from Target Models". If you use any content of this repo for your work, plea

Su Lu 7 Dec 06, 2022
PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules

Dynamic Routing Between Capsules - PyTorch implementation PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules from Sara Sabour,

Adam Bielski 475 Dec 24, 2022
A Learning-based Camera Calibration Toolbox

Learning-based Camera Calibration A Learning-based Camera Calibration Toolbox Paper The pdf file can be found here. @misc{zhang2022learningbased,

Eason 14 Dec 21, 2022
An Unbiased Learning To Rank Algorithms (ULTRA) toolbox

Unbiased Learning to Rank Algorithms (ULTRA) This is an Unbiased Learning To Rank Algorithms (ULTRA) toolbox, which provides a codebase for experiment

back 3 Nov 18, 2022
This is the repository for our paper SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking

SimpleTrack This is the repository for our paper SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking. We are still working on writing t

TuSimple 189 Dec 26, 2022
Neural Fixed-Point Acceleration for Convex Optimization

Licensing The majority of neural-scs is licensed under the CC BY-NC 4.0 License, however, portions of the project are available under separate license

Facebook Research 27 Oct 06, 2022
Pywonderland - A tour in the wonderland of math with python.

A Tour in the Wonderland of Math with Python A collection of python scripts for drawing beautiful figures and animating interesting algorithms in math

Zhao Liang 4.1k Jan 03, 2023
Code for Environment Dynamics Decomposition (ED2).

ED2 Code for Environment Dynamics Decomposition (ED2). Installation Follow the installation in MBPO and Dreamer. Usage First follow the SD2 method for

0 Aug 10, 2021