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06/13/2023
Semi-supervised learning made simple with self-supervised clustering
Self-supervised learning models have been shown to learn rich visual rep...
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05/15/2023
Improved baselines for vision-language pre-training
Contrastive learning has emerged as an efficient framework to learn mult...
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02/18/2023
StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalization
Large-scale foundation models (e.g., CLIP) have shown promising zero-sho...
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12/09/2022
A soft nearest-neighbor framework for continual semi-supervised learning
Despite significant advances, the performance of state-of-the-art contin...
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07/23/2022
Multimodal Emotion Recognition with Modality-Pairwise Unsupervised Contrastive Loss
Emotion recognition is involved in several real-world applications. With...
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03/26/2022
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
A fundamental and challenging problem in deep learning is catastrophic f...
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02/01/2022
Continual Attentive Fusion for Incremental Learning in Semantic Segmentation
Over the past years, semantic segmentation, as many other tasks in compu...
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12/08/2021
Self-Supervised Models are Continual Learners
Self-supervised models have been shown to produce comparable or better v...
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08/19/2021
A Unified Objective for Novel Class Discovery
In this paper, we study the problem of Novel Class Discovery (NCD). NCD ...
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08/03/2021
Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning
This paper presents solo-learn, a library of self-supervised methods for...
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06/20/2021
Neighborhood Contrastive Learning for Novel Class Discovery
In this paper, we address Novel Class Discovery (NCD), the task of unvei...
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08/04/2020
Online Continual Learning under Extreme Memory Constraints
Continual Learning (CL) aims to develop agents emulating the human abili...
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11/04/2019
