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07/18/2023
MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
Self-supervised learning can be used for mitigating the greedy needs of ...
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04/23/2023
You Never Get a Second Chance To Make a Good First Impression: Seeding Active Learning for 3D Semantic Segmentation
We propose SeedAL, a method to seed active learning for efficient annota...
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12/15/2022
Unsupervised Object Localization: Observing the Background to Discover Objects
Recent advances in self-supervised visual representation learning have p...
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07/25/2022
Active Learning Strategies for Weakly-supervised Object Detection
Object detectors trained with weak annotations are affordable alternativ...
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03/21/2022
Drive Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation
This work investigates learning pixel-wise semantic image segmentation i...
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09/29/2021
Localizing Objects with Self-Supervised Transformers and no Labels
Localizing objects in image collections without supervision can help to ...
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11/19/2019
Rethinking deep active learning: Using unlabeled data at model training
Active learning typically focuses on training a model on few labeled exa...
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05/15/2019
Local Features and Visual Words Emerge in Activations
We propose a novel method of deep spatial matching (DSM) for image retri...
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09/14/2017