3rd Place Solution for ICCV 2021 Workshop SSLAD Track 3A - Continual Learning Classification Challenge

Overview

Online Continual Learning via Multiple Deep Metric Learning and Uncertainty-guided Episodic Memory Replay

3rd Place Solution for ICCV 2021 Workshop SSLAD Track 3A - Continual Learning Classification

Technical Report slides
video

Description

Official implementation of our solution (3rd place) for ICCV 2021 Workshop Self-supervised Learning for Next-Generation Industry-level Autonomous Driving (SSLAD) Track 3A - Continual Learning Classification using "Online Continual Learning via Multiple Deep Metric Learning and Uncertainty-guided Episodic Memory Replay".

How to run

First, install dependencies

# clone project   
git clone https://github.com/mrifkikurniawan/sslad.git

# install project   
cd sslad 
pip3 install -r requirements.txt   

Next, preparing the dataset via links below.

Next, run training.

# run training module with our proposed cl strategy
python3.9 classification.py \
--config configs/cl_strategy.yaml \
--name {path/to/log} \
--root {root/of/your/dataset} \
--num_workers {num workers} \
--gpu_id {your-gpu-id} \
--comment {any-comments} 
--store \

or see the train.sh for the example.

Experiments Results

Method Val AMCA Test AMCA
Baseline (Uncertainty Replay)* 57.517 -
+ Multi-step Lr Scheduler* 59.591 (+2.07) -
+ Soft Labels Retrospection* 59.825 (+0.23) -
+ Contrastive Learning* 60.363 (+0.53) 59.68
+ Supervised Contrastive Learning* 61.49 (+1.13) -
+ Change backbone to ResNet50-D* 62.514 (+1.02) -
+ Focal loss* 62.71 (+0.19) -
+ Cost Sensitive Cross Entropy 63.33 (+0.62) -
+ Class Balanced Focal loss* 64.01 (+1.03) 64.53 (+4.85)
+ Head Fine-tuning with Class Balanced Replay 65.291 (+1.28) 62.58 (-1.56)
+ Head Fine-tuning with Soft Labels Retrospection 66.116 (+0.83) 62.97 (+0.39)

*Applied to our final method.

File overview

classification.py: Driver code for the classification subtrack. There are a few things that can be changed here, such as the model, optimizer and loss criterion. There are several arguments that can be set to store results etc. (Run classification.py --help to get an overview, or check the file.)

class_strategy.py: Provides an empty plugin. Here, you can define your own strategy, by implementing the necessary callbacks. Helper methods and classes can be ofcourse implemented as pleased. See here for examples of strategy plugins.

data_intro.ipynb: In this notebook the stream of data is further introduced and explained. Feel free to experiment with the dataset to get a good feeling of the challenge.

Note: not all callbacks have to be implemented, you can just delete those that you don't need.

classification_util.py & haitain_classification.py: These files contain helper code for dataloading etc. There should be no reason to change these.

Owner
Rifki Kurniawan
MS student at Xi'an Jiaotong University; Artificial Intelligence Engineer at Nodeflux
Rifki Kurniawan
Implementation of the Remixer Block from the Remixer paper, in Pytorch

Remixer - Pytorch Implementation of the Remixer Block from the Remixer paper, in Pytorch. It claims that substituting the feedforwards in transformers

Phil Wang 35 Aug 23, 2022
Datasets, tools, and benchmarks for representation learning of code.

The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided

GitHub 1.8k Dec 25, 2022
Does MAML Only Work via Feature Re-use? A Data Set Centric Perspective

Does-MAML-Only-Work-via-Feature-Re-use-A-Data-Set-Centric-Perspective Does MAML Only Work via Feature Re-use? A Data Set Centric Perspective Installin

2 Nov 07, 2022
Bayesian Deep Learning and Deep Reinforcement Learning for Object Shape Error Response and Correction of Manufacturing Systems

Bayesian Deep Learning for Manufacturing 2.0 (dlmfg) Object Shape Error Response (OSER) Digital Lifecycle Management - In Process Quality Improvement

Sumit Sinha 30 Oct 31, 2022
Code for PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Relighting and Material Editing

PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Relighting and Material Editing CVPR 2021. Project page: https://kai-46.github.io/

Kai Zhang 141 Dec 14, 2022
Unsupervised Representation Learning via Neural Activation Coding

Neural Activation Coding This repository contains the code for the paper "Unsupervised Representation Learning via Neural Activation Coding" published

yookoon park 5 May 26, 2022
Unsupervised phone and word segmentation using dynamic programming on self-supervised VQ features.

Unsupervised Phone and Word Segmentation using Vector-Quantized Neural Networks Overview Unsupervised phone and word segmentation on speech data is pe

Herman Kamper 13 Dec 11, 2022
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

LSTMs for Human Activity Recognition Human Activity Recognition (HAR) using smartphones dataset and an LSTM RNN. Classifying the type of movement amon

Guillaume Chevalier 3.1k Dec 30, 2022
Contextual Attention Localization for Offline Handwritten Text Recognition

CALText This repository contains the source code for CALText model introduced in "CALText: Contextual Attention Localization for Offline Handwritten T

0 Feb 17, 2022
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids

PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids The electric grid is a key enabling infrastructure for the a

Texas A&M Engineering Research 19 Jan 07, 2023
Funnels: Exact maximum likelihood with dimensionality reduction.

Funnels This repository contains the code needed to reproduce the experiments from the paper: Funnels: Exact maximum likelihood with dimensionality re

2 Apr 21, 2022
Pytorch implementation of the paper Time-series Generative Adversarial Networks

TimeGAN-pytorch Pytorch implementation of the paper Time-series Generative Adversarial Networks presented at NeurIPS'19. Jinsung Yoon, Daniel Jarrett

Zhiwei ZHANG 21 Nov 24, 2022
On Out-of-distribution Detection with Energy-based Models

On Out-of-distribution Detection with Energy-based Models This repository contains the code for the experiments conducted in the paper On Out-of-distr

Sven 19 Aug 07, 2022
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

8 Nov 14, 2022
Implementation of the Transformer variant proposed in "Transformer Quality in Linear Time"

FLASH - Pytorch Implementation of the Transformer variant proposed in the paper Transformer Quality in Linear Time Install $ pip install FLASH-pytorch

Phil Wang 209 Dec 28, 2022
A minimal TPU compatible Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

NeRF Minimal Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. Result of Tiny-NeRF RGB Depth

Soumik Rakshit 11 Jul 24, 2022
[IJCAI'21] Deep Automatic Natural Image Matting

Deep Automatic Natural Image Matting [IJCAI-21] This is the official repository of the paper Deep Automatic Natural Image Matting. Introduction | Netw

Jizhizi_Li 316 Jan 06, 2023
EssentialMC2 Video Understanding

EssentialMC2 Introduction EssentialMC2 is a complete system to solve video understanding tasks including MHRL(representation learning), MECR2( relatio

Alibaba 106 Dec 11, 2022
Official implementation of "MetaSDF: Meta-learning Signed Distance Functions"

MetaSDF: Meta-learning Signed Distance Functions Project Page | Paper | Data Vincent Sitzmann*, Eric Ryan Chan*, Richard Tucker, Noah Snavely Gordon W

Vincent Sitzmann 100 Jan 01, 2023
SmartSim Infrastructure Library.

Home Install Documentation Slack Invite Cray Labs SmartSim SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and Ten

Cray Labs 139 Jan 01, 2023