Small Object Detection
42 papers with code • 4 benchmarks • 11 datasets
Small Object Detection is a computer vision task that involves detecting and localizing small objects in images or videos. This task is challenging due to the small size and low resolution of the objects, as well as other factors such as occlusion, background clutter, and variations in lighting conditions.
( Image credit: Feature-Fused SSD )
Benchmarks
These leaderboards are used to track progress in Small Object Detection
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Datasets
DOTA
iSAID
RF100
SOD4SB
SODA-A
Aircraft Context Dataset
SODA-D
USC-GRAD-STDdb
Blood Cell Detection Dataset
Most implemented papers
Structure-measure: A New Way to Evaluate Foreground Maps
Our new measure simultaneously evaluates region-aware and object-aware structural similarity between a SM and a GT map.
Feature-Fused SSD: Fast Detection for Small Objects
We propose a multi-level feature fusion method for introducing contextual information in SSD, in order to improve the accuracy for small objects.
MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small Objects
siddhanthaldar/PyTorch_Object_Detection
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The performance of small object detection, however, is still less than satisfactory because of the deficiency of semantic information on shallow feature maps.
Extended Feature Pyramid Network for Small Object Detection
Small object detection remains an unsolved challenge because it is hard to extract information of small objects with only a few pixels.
Reducing Label Noise in Anchor-Free Object Detection
nerminsamet/ppdet
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BMVC 2020
In this paper, we propose a new labeling strategy aimed to reduce the label noise in anchor-free detectors.
1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track
NaCl-Ocean/Anchor_free_detection_rotation
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In this technical report, we present our solutions of Waymo Open Dataset (WOD) Challenge 2020 - 2D Object Track.
Mind the Pad -- CNNs can Develop Blind Spots
We show how feature maps in convolutional networks are susceptible to spatial bias.
A Method for Detection of Small Moving Objects in UAV Videos
To circumvent this problem, we propose training a CNN using synthetic videos generated by adding small blob-like objects to video sequences with real-world backgrounds.
QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection
ChenhongyiYang/QueryDet-PyTorch
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CVPR 2022
On the popular COCO dataset, the proposed method improves the detection mAP by 1. 0 and mAP-small by 2. 0, and the high-resolution inference speed is improved to 3. 0x on average.
FOVEA: Foveated Image Magnification for Autonomous Navigation
Efficient processing of high-res video streams is safety-critical for many robotics applications such as autonomous driving.
