Search Results for author:
Found 6 papers, 3 papers with code
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data
Anomaly detection in real-world scenarios poses challenges due to dynamic and often unknown anomaly distributions, requiring robust methods that operate under an open-world assumption.
A Reinforcement Learning Approach for Sequential Spatial Transformer Networks
Spatial Transformer Networks (STN) can generate geometric transformations which modify input images to improve the classifier's performance.
Hybrid-S2S: Video Object Segmentation with Recurrent Networks and Correspondence Matching
In this work, we study an RNN-based architecture and address some of these issues by proposing a hybrid sequence-to-sequence architecture named HS2S, utilizing a dual mask propagation strategy that allows incorporating the information obtained from correspondence matching.
Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory
Video Object Segmentation (VOS) is an active research area of the visual domain.
P $\approx$ NP, at least in Visual Question Answering
In recent years, progress in the Visual Question Answering (VQA) field has largely been driven by public challenges and large datasets.
Adversarial Defense based on Structure-to-Signal Autoencoders
We analyze their robustness against several white-box and gray-box scenarios on the large ImageNet dataset.
