SOTAVerified

Small Object Detection

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 )

Papers

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Showing 141–150 of 152 papers

TitleStatusHype
Small traffic sign detection from large image—0
The Power of Tiling for Small Object Detection—0
Multiple receptive fields and small-object-focusing weakly-supervised segmentation network for fast object detection—0
SOD-MTGAN: Small Object Detection via Multi-Task Generative Adversarial Network—0
MITOS-RCNN: A Novel Approach to Mitotic Figure Detection in Breast Cancer Histopathology Images using Region Based Convolutional Neural Networks—0
MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small ObjectsCode0
Feature Selective Small Object Detection via Knowledge-based Recurrent Attentive Neural Network—0
3D Regression Neural Network for the Quantification of Enlarged Perivascular Spaces in Brain MRI—0
Feature-Fused SSD: Fast Detection for Small ObjectsCode0
Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects—0
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All datasetsSOD4SB Private TestSOD4SB Public TestBee4Exp Honeybee DetectionSODA-D

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Weighted Box Fusion (WBF)AP5030.3—Unverified
2GFL + Test Time AugmentationAP5023.7—Unverified
3DL method (YOLOv8 + Ensamble)AP5022.9—Unverified
4Swin Transformer + Hierarchical designAP5022.6—Unverified
5E2 method (Normalized Gaussian Wasserstein Distance + Switch Hard Augmentation + Multi scale train + Weight Moving Average + CenterNet + VarifocalNet)AP5022.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Weighted Box Fusion (WBF)AP5077.6—Unverified
2GFL + Test Time AugmentationAP5073.1—Unverified
3DL method (YOLOv8 + Ensamble)AP5073.1—Unverified
4Swin Transformer + Hierarchical designAP5070.2—Unverified
5E2 method (Normalized Gaussian Wasserstein Distance + Switch Hard Augmentation + Multi scale train + Weight Moving Average + CenterNet + VarifocalNet)AP5069.6—Unverified
#ModelMetricClaimedVerifiedStatus
1BeeDetectorAverage F10.86—Unverified
#ModelMetricClaimedVerifiedStatus
1CFINetmAP@0.5:0.9530.7—Unverified