Incremental Learning

129 papers with code • 13 benchmarks • 7 datasets

Incremental learning aims to develop artificially intelligent systems that can continuously learn to address new tasks from new data while preserving knowledge learned from previously learned tasks.

Greatest papers with code

Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly Detection

numenta/NAB 25 Jan 2016

We present a novel algorithm for anomaly detection on very large datasets and data streams.

Anomaly Detection Incremental Learning

Distractor-aware Siamese Networks for Visual Object Tracking

foolwood/DaSiamRPN ECCV 2018

During the off-line training phase, an effective sampling strategy is introduced to control this distribution and make the model focus on the semantic distractors.

Incremental Learning Visual Object Tracking +1

Three scenarios for continual learning

GMvandeVen/continual-learning 15 Apr 2019

Standard artificial neural networks suffer from the well-known issue of catastrophic forgetting, making continual or lifelong learning difficult for machine learning.

class-incremental learning Incremental Learning

Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns

ahangchen/TFusion CVPR 2018

Most of the proposed person re-identification algorithms conduct supervised training and testing on single labeled datasets with small size, so directly deploying these trained models to a large-scale real-world camera network may lead to poor performance due to underfitting.

Incremental Learning Learning-To-Rank +2

Adaptive Aggregation Networks for Class-Incremental Learning

yaoyao-liu/class-incremental-learning CVPR 2021

Class-Incremental Learning (CIL) aims to learn a classification model with the number of classes increasing phase-by-phase.

class-incremental learning Incremental Learning

Mnemonics Training: Multi-Class Incremental Learning without Forgetting

yaoyao-liu/mnemonics CVPR 2020

However, there is an inherent trade-off to effectively learning new concepts without catastrophic forgetting of previous ones.

class-incremental learning Incremental Learning

iCaRL: Incremental Classifier and Representation Learning

yaoyao-liu/mnemonics CVPR 2017

A major open problem on the road to artificial intelligence is the development of incrementally learning systems that learn about more and more concepts over time from a stream of data.

Incremental Learning Representation Learning

A cognitive neural architecture able to learn and communicate through natural language

golosio/annabell 10 Jun 2015

Communicative interactions involve a kind of procedural knowledge that is used by the human brain for processing verbal and nonverbal inputs and for language production.

Incremental Learning

PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning

arthurdouillard/incremental_learning.pytorch ECCV 2020

Lifelong learning has attracted much attention, but existing works still struggle to fight catastrophic forgetting and accumulate knowledge over long stretches of incremental learning.

class-incremental learning Incremental Learning +1

A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks

pokaxpoka/deep_Mahalanobis_detector NeurIPS 2018

Detecting test samples drawn sufficiently far away from the training distribution statistically or adversarially is a fundamental requirement for deploying a good classifier in many real-world machine learning applications.

class-incremental learning Incremental Learning +1