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 26–50 of 152 papers

TitleStatusHype
Unleashing the Power of Generic Segmentation Models: A Simple Baseline for Infrared Small Target DetectionCode1
BFA-YOLO: A balanced multiscale object detection network for building façade attachments detection—0
Small Object Detection for Indoor Assistance to the Blind using YOLO NAS Small and Super Gradients—0
A Lightweight Insulator Defect Detection Model Based on Drone ImagesCode1
IDD-YOLOv5: A Lightweight Insulator Defect Real-time Detection AlgorithmCode0
Enhancing Object Detection with Hybrid dataset in Manufacturing Environments: Comparing Federated Learning to Conventional Techniques—0
Infra-YOLO: Efficient Neural Network Structure with Model Compression for Real-Time Infrared Small Object Detection—0
SOD-YOLOv8 -- Enhancing YOLOv8 for Small Object Detection in Traffic ScenesCode1
Cross-Layer Feature Pyramid Transformer for Small Object Detection in Aerial ImagesCode2
XS-VID: An Extremely Small Video Object Detection Dataset—0
ESOD: Efficient Small Object Detection on High-Resolution ImagesCode2
Visible-Thermal Tiny Object Detection: A Benchmark Dataset and BaselinesCode3
DASSF: Dynamic-Attention Scale-Sequence Fusion for Aerial Object Detection—0
MWIRSTD: A MWIR Small Target Detection DatasetCode1
Sense Less, Generate More: Pre-training LiDAR Perception with Masked Autoencoders for Ultra-Efficient 3D SensingCode0
Select-Mosaic: Data Augmentation Method for Dense Small Object ScenesCode0
SOAR: Advancements in Small Body Object Detection for Aerial Imagery Using State Space Models and Programmable Gradients—0
Constellation Dataset: Benchmarking High-Altitude Object Detection for an Urban IntersectionCode1
FOOL: Addressing the Downlink Bottleneck in Satellite Computing with Neural Feature CompressionCode1
HCF-Net: Hierarchical Context Fusion Network for Infrared Small Object DetectionCode2
FLAME Diffuser: Wildfire Image Synthesis using Mask Guided DiffusionCode1
YOLO-TLA: An Efficient and Lightweight Small Object Detection Model based on YOLOv5—0
YOLO-Ant: A Lightweight Detector via Depthwise Separable Convolutional and Large Kernel Design for Antenna Interference Source DetectionCode0
Small Object Detection by DETR via Information Augmentation and Adaptive Feature Fusion—0
Dr^2Net: Dynamic Reversible Dual-Residual Networks for Memory-Efficient FinetuningCode0
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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
2DL method (YOLOv8 + Ensamble)AP5073.1—Unverified
3GFL + Test Time AugmentationAP5073.1—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