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08/22/2023
Time Does Tell: Self-Supervised Time-Tuning of Dense Image Representations
Spatially dense self-supervised learning is a rapidly growing problem do...
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10/25/2022
InForecaster: Forecasting Influenza Hemagglutinin Mutations Through the Lens of Anomaly Detection
The influenza virus hemagglutinin is an important part of the virus atta...
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06/09/2022
SwinCheX: Multi-label classification on chest X-ray images with transformers
According to the considerable growth in the avail of chest X-ray images ...
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05/28/2022
Fake It Till You Make It: Near-Distribution Novelty Detection by Score-Based Generative Models
We aim for image-based novelty detection. Despite considerable progress,...
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05/24/2022
Attentional Mixtures of Soft Prompt Tuning for Parameter-efficient Multi-task Knowledge Sharing
This work introduces ATTEMPT (Attentional Mixture of Prompt Tuning), a n...
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10/26/2021
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges
Machine learning models often encounter samples that are diverged from t...
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03/18/2021
Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomalies
Video anomaly detection has proved to be a challenging task owing to its...
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11/22/2020
Multiresolution Knowledge Distillation for Anomaly Detection
Unsupervised representation learning has proved to be a critical compone...
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08/29/2020
Puzzle-AE: Novelty Detection in Images through Solving Puzzles
Autoencoder (AE) has proved to be an effective framework for novelty det...
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03/12/2020
