Jan 31, 2021 · Based on Faster R-CNN, we explore some effective and general methods to improve the detection performance of tiny objects.
Based on Faster R-CNN, we explore some effective and general methods to improve the detection performance of tiny objects. Since the model architectures will ...
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This paper turns to knowledge distillation to improve the representation learning of a small model regarding both superior detection accuracy and fast ...
In this paper, we present our solution of the 1st Tiny Object Detection (TOD) Challenge. The purpose of the challenge is to detect tiny person objects (2–20 ...
May 3, 2024 · The paper proposes two modules: the MDFFAM (Multi-Directional Feature Fusion Attention Mechanism) and the LKSPP (Large Kernel Spatial Pyramid Pooling),
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Oct 6, 2020 · The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in ...
May 20, 2024 · Here, we will explore various techniques and strategies to enhance the detection of small objects in images.
Therefore, we can propose a feasible method to improve the tiny-objects detection performance by changing the network structure on one hand and expanding the ...
A good data set can effectively improve the performance of object detection, but most of the early object detection data sets are images of large and medium- ...
It uses the Region Proposal Network (RPN) to generate candidate regions instead of selective search, which greatly reduces the detection time and improves the ...