research
∙
09/12/2023
Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning
Continuous unsupervised representation learning (CURL) research has grea...
share
research
∙
09/06/2023
Continual Evidential Deep Learning for Out-of-Distribution Detection
Uncertainty-based deep learning models have attracted a great deal of in...
research
∙
09/01/2023
Trust your Good Friends: Source-free Domain Adaptation by Reciprocal Neighborhood Clustering
Domain adaptation (DA) aims to alleviate the domain shift between source...
research
∙
08/31/2023
ScrollNet: Dynamic Weight Importance for Continual Learning
The principle underlying most existing continual learning (CL) methods i...
research
∙
08/20/2023
A Comprehensive Empirical Evaluation on Online Continual Learning
Online continual learning aims to get closer to a live learning experien...
research
∙
07/23/2023
Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection
In incremental learning, replaying stored samples from previous tasks to...
research
∙
06/29/2023
Improving Online Continual Learning Performance and Stability with Temporal Ensembles
Neural networks are very effective when trained on large datasets for a ...
research
∙
04/11/2023
Density Map Distillation for Incremental Object Counting
We investigate the problem of incremental learning for object counting, ...
research
∙
03/28/2023
Projected Latent Distillation for Data-Agnostic Consolidation in Distributed Continual Learning
Distributed learning on the edge often comprises self-centered devices (...
research
∙
03/28/2023
StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing
A significant research effort is focused on exploiting the amazing capac...
research
∙
03/27/2023
3D-Aware Multi-Class Image-to-Image Translation with NeRFs
Recent advances in 3D-aware generative models (3D-aware GANs) combined w...
research
∙
03/14/2023
ICICLE: Interpretable Class Incremental Continual Learning
Continual learning enables incremental learning of new tasks without for...
research
∙
02/01/2023
Towards Label-Efficient Incremental Learning: A Survey
The current dominant paradigm when building a machine learning model is ...
research
∙
11/22/2022
Gated Class-Attention with Cascaded Feature Drift Compensation for Exemplar-free Continual Learning of Vision Transformers
In this paper we propose a new method for exemplar-free class incrementa...
research
∙
10/13/2022
Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation
In class-incremental semantic segmentation (CISS), deep learning archite...
research
∙
10/04/2022
Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification
Lifelong object re-identification incrementally learns from a stream of ...
research
∙
10/03/2022
Attention Distillation: self-supervised vision transformer students need more guidance
Self-supervised learning has been widely applied to train high-quality v...
research
∙
06/07/2022
One Ring to Bring Them All: Towards Open-Set Recognition under Domain Shift
In this paper, we investigate open-set recognition with domain shift, wh...
research
∙
05/30/2022
MVMO: A Multi-Object Dataset for Wide Baseline Multi-View Semantic Segmentation
We present MVMO (Multi-View, Multi-Object dataset): a synthetic dataset ...
research
∙
05/09/2022
Local Prediction Aggregation: A Frustratingly Easy Source-free Domain Adaptation Method
We propose a simple but effective source-free domain adaptation (SFDA) m...
research
∙
02/16/2022
Planckian jitter: enhancing the color quality of self-supervised visual representations
Several recent works on self-supervised learning are trained by mapping ...
research
∙
01/25/2022
Main Product Detection with Graph Networks for Fashion
Computer vision has established a foothold in the online fashion retail ...
research
∙
12/30/2021
Continually Learning Self-Supervised Representations with Projected Functional Regularization
Recent self-supervised learning methods are able to learn high-quality i...
research
∙
12/10/2021
Visual Transformers with Primal Object Queries for Multi-Label Image Classification
Multi-label image classification is about predicting a set of class labe...
research
∙
12/04/2021
Hyper-GAN: Transferring Unconditional to Conditional GANs with HyperNetworks
Conditional GANs have matured in recent years and are able to generate h...
research
∙
11/09/2021
Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition
Most meta-learning approaches assume the existence of a very large set o...
research
∙
10/21/2021
HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification
Human beings learn and accumulate hierarchical knowledge over their life...
research
∙
10/09/2021
Class-Balanced Active Learning for Image Classification
Active learning aims to reduce the labeling effort that is required to t...
research
∙
10/08/2021
Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation
Domain adaptation (DA) aims to alleviate the domain shift between source...
research
∙
08/25/2021
Reducing Label Effort: Self-Supervised meets Active Learning
Active learning is a paradigm aimed at reducing the annotation effort by...
research
∙
08/03/2021
Generalized Source-free Domain Adaptation
Domain adaptation (DA) aims to transfer the knowledge learned from a sou...
research
∙
07/30/2021
When Deep Learners Change Their Mind: Learning Dynamics for Active Learning
Active learning aims to select samples to be annotated that yield the la...
research
∙
05/18/2021
ACAE-REMIND for Online Continual Learning with Compressed Feature Replay
Online continual learning aims to learn from a non-IID stream of data fr...
research
∙
05/13/2021
TransferI2I: Transfer Learning for Image-to-Image Translation from Small Datasets
Image-to-image (I2I) translation has matured in recent years and is able...
research
∙
04/28/2021
MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains
GANs largely increases the potential impact of generative models. Theref...
research
∙
04/14/2021
Continual learning in cross-modal retrieval
Multimodal representations and continual learning are two areas closely ...
research
∙
03/08/2021
On Implicit Attribute Localization for Generalized Zero-Shot Learning
Zero-shot learning (ZSL) aims to discriminate images from unseen classes...
research
∙
01/27/2021
Generative Multi-Label Zero-Shot Learning
Multi-label zero-shot learning strives to classify images into multiple ...
research
∙
12/06/2020
Self-Training for Class-Incremental Semantic Segmentation
We study incremental learning for semantic segmentation where when learn...
research
∙
11/11/2020
DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs
Image-to-image translation has recently achieved remarkable results. But...
research
∙
10/23/2020
Unsupervised Domain Adaptation without Source Data by Casting a BAIT
Unsupervised domain adaptation (UDA) aims to transfer the knowledge lear...
research
∙
07/31/2020
Learning to Rank for Active Learning: A Listwise Approach
Active learning emerged as an alternative to alleviate the effort to lab...
research
∙
07/24/2020
Hallucinating Saliency Maps for Fine-Grained Image Classification for Limited Data Domains
Most of the saliency methods are evaluated on their ability to generate ...
research
∙
07/13/2020
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning
Research on continual learning has led to a variety of approaches to mit...
research
∙
06/26/2020
Bookworm continual learning: beyond zero-shot learning and continual learning
We propose bookworm continual learning(BCL), a flexible setting where un...
research
∙
06/10/2020
Simple and effective localized attribute representations for zero-shot learning
Zero-shot learning (ZSL) aims to discriminate images from unseen classes...
research
∙
04/22/2020
Distributed Learning and Inference with Compressed Images
Modern computer vision requires processing large amounts of data, both w...
research
∙
04/20/2020
Generative Feature Replay For Class-Incremental Learning
Humans are capable of learning new tasks without forgetting previous one...
research
∙
04/01/2020
Semantic Drift Compensation for Class-Incremental Learning
Class-incremental learning of deep networks sequentially increases the n...
research
∙
03/30/2020
