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
3D Small Object Detection with Dynamic Spatial PruningCode1
UIU-Net: U-Net in U-Net for Infrared Small Object DetectionCode1
Large, Complex, and Realistic Safety Clothing and Helmet Detection: Dataset and MethodCode1
LSTFE-Net:Long Short-Term Feature Enhancement Network for Video Small Object DetectionCode1
Structure-measure: A New Way to Evaluate Foreground MapsCode1
Towards Scene Understanding for Autonomous Operations on Airport ApronsCode1
FOOL: Addressing the Downlink Bottleneck in Satellite Computing with Neural Feature CompressionCode1
A Method for Detection of Small Moving Objects in UAV VideosCode1
FOVEA: Foveated Image Magnification for Autonomous NavigationCode1
A Comprehensive Approach for UAV Small Object Detection with Simulation-based Transfer Learning and Adaptive FusionCode1
HIC-YOLOv5: Improved YOLOv5 For Small Object DetectionCode1
Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature IntegrationCode1
Local Contrast and Global Contextual Information Make Infrared Small Object Salient AgainCode1
FLAME Diffuser: Wildfire Image Synthesis using Mask Guided DiffusionCode1
Augmentation for small object detectionCode1
Cascaded Zoom-in Detector for High Resolution Aerial ImagesCode1
Multimodal Transformer Using Cross-Channel attention for Object Detection in Remote Sensing ImagesCode1
Anchor Retouching via Model Interaction for Robust Object Detection in Aerial ImagesCode1
PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplanar MRI SlicesCode1
QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object DetectionCode1
Transformers in Small Object Detection: A Benchmark and Survey of State-of-the-ArtCode1
Deep Learning-Based Object Detection in Maritime Unmanned Aerial Vehicle Imagery: Review and Experimental ComparisonsCode0
Small Object Detection via Pixel Level Balancing With Applications to Blood Cell DetectionCode0
Select-Mosaic: Data Augmentation Method for Dense Small Object ScenesCode0
Sense Less, Generate More: Pre-training LiDAR Perception with Masked Autoencoders for Ultra-Efficient 3D SensingCode0
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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