Karsten Roth | DeepAI

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∙ 06/12/2023

Waffling around for Performance: Visual Classification with Random Words and Broad Concepts

The visual classification performance of vision-language models such as ...

0 Karsten Roth, et al. ∙

∙ 05/22/2023

If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection

Despite their impressive capabilities, diffusion-based text-to-image (T2...

0 Shyamgopal Karthik, et al. ∙

∙ 11/06/2022

Momentum-based Weight Interpolation of Strong Zero-Shot Models for Continual Learning

Large pre-trained, zero-shot capable models have shown considerable succ...

0 Zafir Stojanovski, et al. ∙

∙ 10/13/2022

Disentanglement of Correlated Factors via Hausdorff Factorized Support

A grand goal in deep learning research is to learn representations capab...

35 Karsten Roth, et al. ∙

∙ 07/08/2022

A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning

Proxy-based Deep Metric Learning (DML) learns deep representations by em...

0 Michael Kirchhof, et al. ∙

∙ 03/23/2022

Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning

Deep metric learning (DML) enables learning with less supervision throug...

0 Natalie Dullerud, et al. ∙

∙ 03/23/2022

Improving the Fairness of Chest X-ray Classifiers

Deep learning models have reached or surpassed human-level performance i...

0 Haoran Zhang, et al. ∙

∙ 03/16/2022

Non-isotropy Regularization for Proxy-based Deep Metric Learning

Deep Metric Learning (DML) aims to learn representation spaces on which ...

17 Karsten Roth, et al. ∙

∙ 03/16/2022

Integrating Language Guidance into Vision-based Deep Metric Learning

Deep Metric Learning (DML) proposes to learn metric spaces which encode ...

9 Karsten Roth, et al. ∙

∙ 07/20/2021

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning

Deep Metric Learning (DML) aims to find representations suitable for zer...

17 Timo Milbich, et al. ∙

∙ 06/15/2021

Towards Total Recall in Industrial Anomaly Detection

Being able to spot defective parts is a critical component in large-scal...

8 Karsten Roth, et al. ∙

∙ 09/17/2020

S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning

Deep Metric Learning (DML) provides a crucial tool for visual similarity...

16 Karsten Roth, et al. ∙

∙ 06/22/2020

COVID-19 Image Data Collection: Prospective Predictions Are the Future

Across the world's coronavirus disease 2019 (COVID-19) hot spots, the ne...

11 Joseph Paul Cohen, et al. ∙

∙ 05/24/2020

Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning

The need to streamline patient management for COVID-19 has become more p...

0 Joseph Paul Cohen, et al. ∙

∙ 04/28/2020

DiVA: Diverse Visual Feature Aggregation forDeep Metric Learning

Visual Similarity plays an important role in many computer vision applic...

3 Timo Milbich, et al. ∙

∙ 04/28/2020

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning

Visual Similarity plays an important role in many computer vision applic...

0 Timo Milbich, et al. ∙

∙ 04/12/2020

Sharing Matters for Generalization in Deep Metric Learning

Learning the similarity between images constitutes the foundation for nu...

58 Timo Milbich, et al. ∙

∙ 03/24/2020

PADS: Policy-Adapted Sampling for Visual Similarity Learning

Learning visual similarity requires to learn relations, typically betwee...

1 Karsten Roth, et al. ∙

∙ 02/19/2020

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning

Deep Metric Learning (DML) is arguably one of the most influential lines...

0 Karsten Roth, et al. ∙

∙ 09/25/2019

MIC: Mining Interclass Characteristics for Improved Metric Learning

Metric learning seeks to embed images of objects suchthat class-defined ...

6 Karsten Roth, et al. ∙

∙ 08/14/2019

Boosting Liver and Lesion Segmentation from CT Scans By Mask Mining

In this paper we propose a novel procedure to improve liver and liver le...

0 Karsten Roth, et al. ∙

∙ 05/09/2019

Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss function

At present, lesion segmentation is still performed manually (or semi-aut...

0 Karsten Roth, et al. ∙

∙ 01/13/2019

The Liver Tumor Segmentation Benchmark (LiTS)

In this work, we report the set-up and results of the Liver Tumor Segmen...

8 Patrick Bilic, et al. ∙

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