The official PyTorch code for NeurIPS 2021 ML4AD Paper, "Does Thermal data make the detection systems more reliable?"

Related tags

Deep LearningMMC
Overview

MultiModal-Collaborative (MMC) Learning Framework for integrating RGB and Thermal spectral modalities

This is the official code for NeurIPS 2021 Machine Learning for Autonomous Driving Workshop Paper, "Does Thermal data make the detection systems more reliable?" by Shruthi Gowda, Elahe Arani and Bahram Zonooz.

Methodology

Architecture

Detection Head : SSD
Detection Backbone : Resnet (CNN-based) or DEiT (Transformer-based)

MMC framework

image info

MMC framework has multiple versions

KD.ENABLE: True
KD.ENABLE_DML: True

1. MMC (Base Version) : Det Loss + DML Loss 
    KD.DISTILL_TYPE : KL, AT, L2, L2B
    KL (KL divergence), AT (Attention loss), L2 (L2 norm at head layer), L2B (L2 norm of backbone features)
   
2. MMC v1 (Reconstruction) : Det Loss + DML Loss + Recon Loss
    KD.AUX_RECON = True
    KD.AUX_RECON_MODE = "normal"

3. MMC v2 (Cross Reconstruction) : Det Loss + DML Loss + Cross Recon Loss
    KD.AUX_RECON = True
    KD.AUX_RECON_MODE = "cross"

We also try other techniques for comparison image info

Fusion
1. Input Fusion
    KD.CONCAT_INPUT
2. Feature Fusion
    KD.CONCAT_FEATURES
    CONCAT_LAYERS

Installation

You can prepare the environment using:

pip install -r requirements.txt

You can build the project using the following script:

./build {conda_env_name}

Datasets

Two datasets "FLIR" and "KAIST" are used in this repo

FLIR : https://www.flir.eu/oem/adas/adas-dataset-form/

KAIST : https://soonminhwang.github.io/rgbt-ped-detection/

Running

Train

There are 2 networks, one receiving RGB images and one receiving thermal images. Both require different config files.

python train.py --config-file <thermal-config-file> --teacher-config-file <rgb-config-file>

Test

For evaluation only one network is used - the first network (RGB or Teacher network)

python test.py --config-file <config-file> --ckpt <model_final.pth>

Model Checkpoints

Cite Our Work

License

This project is licensed under the terms of the MIT license.

Owner
NeurAI
Located at the brain port of Netherlands, the Advanced Research Lab is an innovation center within the NavInfo group. We have a diverse energetic team of resear
NeurAI
GitHub Repository
Non-stationary GP package written from scratch in PyTorch

NSGP-Torch Examples gpytorch model with skgpytorch # Import packages import torch from regdata import NonStat2D from gpytorch.kernels import RBFKernel

Zeel B Patel 1 Mar 06, 2022
GANTheftAuto is a fork of the Nvidia's GameGAN

Description GANTheftAuto is a fork of the Nvidia's GameGAN, which is research focused on emulating dynamic game environments. The early research done

Harrison 801 Dec 27, 2022
This is a repository for a semantic segmentation inference API using the OpenVINO toolkit

BMW-IntelOpenVINO-Segmentation-Inference-API This is a repository for a semantic segmentation inference API using the OpenVINO toolkit. It's supported

BMW TechOffice MUNICH 34 Nov 24, 2022
Answering Open-Domain Questions of Varying Reasoning Steps from Text

This repository contains the authors' implementation of the Iterative Retriever, Reader, and Reranker (IRRR) model in the EMNLP 2021 paper "Answering Open-Domain Questions of Varying Reasoning Steps

26 Dec 22, 2022
GAN-based Matrix Factorization for Recommender Systems

GAN-based Matrix Factorization for Recommender Systems This repository contains the datasets' splits, the source code of the experiments and their res

Ervin Dervishaj 9 Nov 06, 2022
A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

24 Dec 13, 2022
LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021

LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021 We propose a cross encoder model (LTR_CrossEncoder) for information retrieval, re-retrie

Hieu Duong 7 Jan 12, 2022
Code for the paper: Sketch Your Own GAN

Sketch Your Own GAN Project | Paper | Youtube Our method takes in one or a few hand-drawn sketches and customizes an off-the-shelf GAN to match the in

677 Dec 28, 2022
[Link]deep_portfolo - Use Reforcemet earg ad Supervsed learg to Optmze portfolo allocato []

rl_portfolio This Repository uses Reinforcement Learning and Supervised learning to Optimize portfolio allocation. The goal is to make profitable agen

Deepender Singla 165 Dec 02, 2022
Pytorch Implementation for Dilated Continuous Random Field

DilatedCRF Pytorch implementation for fully-learnable DilatedCRF. If you find my work helpful, please consider our paper: @article{Mo2022dilatedcrf,

DunnoCoding_Plus 3 Nov 13, 2022
Seach Losses of our paper 'Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search', accepted by ICLR 2021.

CSE-Autoloss Designing proper loss functions for vision tasks has been a long-standing research direction to advance the capability of existing models

Peidong Liu(刘沛东) 54 Dec 17, 2022
a minimal terminal with python 😎😉

Meterm a terminal with python 😎 How to use Clone Project: $ git clone https://github.com/motahharm/meterm.git Run: in Terminal: meterm.exe Or pip ins

Motahhar.Mokfi 5 Jan 28, 2022
Automatically creates genre collections for your Plex media

Plex Auto Genres Plex Auto Genres is a simple script that will add genre collection tags to your media making it much easier to search for genre speci

Shane Israel 63 Dec 31, 2022
kapre: Keras Audio Preprocessors

Kapre Keras Audio Preprocessors - compute STFT, ISTFT, Melspectrogram, and others on GPU real-time. Tested on Python 3.6 and 3.7 Why Kapre? vs. Pre-co

Keunwoo Choi 867 Dec 29, 2022
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond

CRF - Conditional Random Fields A library for dense conditional random fields (CRFs). This is the official accompanying code for the paper Regularized

Đ.Khuê Lê-Huu 21 Nov 26, 2022
Deep Residual Networks with 1K Layers

Deep Residual Networks with 1K Layers By Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Microsoft Research Asia (MSRA). Table of Contents Introduc

Kaiming He 856 Jan 06, 2023
Density-aware Single Image De-raining using a Multi-stream Dense Network (CVPR 2018)

DID-MDN Density-aware Single Image De-raining using a Multi-stream Dense Network He Zhang, Vishal M. Patel [Paper Link] (CVPR'18) We present a novel d

He Zhang 224 Dec 12, 2022
In this project, two programs can help you take full agvantage of time on the model training with a remote server

In this project, two programs can help you take full agvantage of time on the model training with a remote server, which can push notification to your phone about the information during model trainin

GrayLee 8 Dec 27, 2022
Gif-caption - A straightforward GIF Captioner written in Python

Broksy's GIF Captioner Have you ever wanted to easily caption a GIF without havi

3 Apr 09, 2022
Magisk module to enable hidden features on Android 12 Developer Preview 1.

Android 12 Extensions This is a Magisk module that enables hidden features on Android 12 Developer Preview 1. Features Scrolling screenshots Wallpaper

Danny Lin 384 Jan 06, 2023