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02/13/2023
In Search for a Generalizable Method for Source Free Domain Adaptation
Source-free domain adaptation (SFDA) is compelling because it allows ada...
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01/20/2023
Open-Set Likelihood Maximization for Few-Shot Learning
We tackle the Few-Shot Open-Set Recognition (FSOSR) problem, i.e. classi...
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11/25/2022
A Strong Baseline for Generalized Few-Shot Semantic Segmentation
This paper introduces a generalized few-shot segmentation framework with...
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10/26/2022
Towards Practical Few-Shot Query Sets: Transductive Minimum Description Length Inference
Standard few-shot benchmarks are often built upon simplifying assumption...
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07/30/2022
Simplex Clustering via sBeta with Applications to Online Adjustment of Black-Box Predictions
We explore clustering the softmax predictions of deep neural networks an...
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06/18/2022
Model-Agnostic Few-Shot Open-Set Recognition
We tackle the Few-Shot Open-Set Recognition (FSOSR) problem, i.e. classi...
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05/31/2022
FHIST: A Benchmark for Few-shot Classification of Histological Images
Few-shot learning has recently attracted wide interest in image classifi...
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04/24/2022
Realistic Evaluation of Transductive Few-Shot Learning
Transductive inference is widely used in few-shot learning, as it levera...
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02/14/2022
KNIFE: Kernelized-Neural Differential Entropy Estimation
Mutual Information (MI) has been widely used as a loss regularizer for t...
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01/15/2022
Parameter-free Online Test-time Adaptation
Training state-of-the-art vision models has become prohibitively expensi...
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06/23/2021
Mutual-Information Based Few-Shot Classification
We introduce Transductive Infomation Maximization (TIM) for few-shot lea...
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06/12/2021
Adversarial Robustness via Fisher-Rao Regularization
Adversarial robustness has become a topic of growing interest in machine...
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12/11/2020
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?
Few-shot segmentation has recently attracted substantial interest, with ...
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08/25/2020
