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08/18/2023
Meta-ZSDETR: Zero-shot DETR with Meta-learning
Zero-shot object detection aims to localize and recognize objects of uns...
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07/31/2023
HiREN: Towards Higher Supervision Quality for Better Scene Text Image Super-Resolution
Scene text image super-resolution (STISR) is an important pre-processing...
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07/26/2023
Flexible Differentially Private Vertical Federated Learning with Adaptive Feature Embeddings
The emergence of vertical federated learning (VFL) has stimulated concer...
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07/20/2023
Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies, and Opportunities
With the increasing amount of spatial-temporal (ST) ocean data, numerous...
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07/04/2023
All in One: Multi-task Prompting for Graph Neural Networks
Recently, ”pre-training and fine-tuning” has been adopted as a standard ...
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03/13/2023
Molecular Property Prediction by Semantic-invariant Contrastive Learning
Contrastive learning have been widely used as pretext tasks for self-sup...
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10/08/2022
Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method
Few-shot object detection (FSOD) is to detect objects with a few example...
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04/24/2022
EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text Classification
Recent works have empirically shown the effectiveness of data augmentati...
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03/27/2022
An Empirical Study and Comparison of Recent Few-Shot Object Detection Algorithms
The generic object detection (GOD) task has been successfully tackled by...
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02/09/2022
ARIBA: Towards Accurate and Robust Identification of Backdoor Attacks in Federated Learning
The distributed nature and privacy-preserving characteristics of federat...
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03/17/2019
Learning Competitive and Discriminative Reconstructions for Anomaly Detection
Most of the existing methods for anomaly detection use only positive dat...
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06/22/2018
Global Semantic Consistency for Zero-Shot Learning
In image recognition, there are many cases where training samples cannot...
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10/07/2011
