Mar 27, 2022 · A comprehensive survey with performance comparison is conducted on recent achievements of FSOD. Furthermore, we also analyze the technical challenges.
An empirical study and comparison has been conducted on the recent achievements of FSOD, and a new taxonomy is proposed based on the role of prior knowledge ...
The generic object detection (GOD) task has been successfully tackled by recent deep neural networks, trained by an avalanche of annotated training samples ...
Oct 30, 2021 · This survey provides a comprehensive overview from current classic and latest achievements for few-shot object detection to future research expectations.
Missing: Empirical Comparison
We review the existing FSOD algorithms from a new perspective under a new taxonomy based on their contributions, ie, data-oriented, model-oriented, and ...
Sep 11, 2024 · ... An Empirical Study and Comparison of Recent Few-Shot Object Detection Algorithms. March 2022. Tianying Liu · Lu Zhang · Yang ...
This survey provides a comprehensive overview from current classic and latest achievements for few-shot object detection to future research expectations.
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An Empirical Study and Comparison of Recent Few-Shot Object Detection Algorithms. Tianyi Liu, Lu Zhang, Yang Wang, J. Guan, Yanwei Fu, Shuigeng Zhou. 2022 ...
In this survey, we aim to provide an overview of state-of- the-art FSOD approaches for new researchers in this emerg- ing research field. First, we define the ...
Latest studies on few-shot object detection (FSOD) mainly focuses on achieving better performance in novel class through few-shot fine-tuning. This approach is ...