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 1–25 of 152 papers

TitleStatusHype
VME: A Satellite Imagery Dataset and Benchmark for Detecting Vehicles in the Middle East and BeyondCode0
Active-O3: Empowering Multimodal Large Language Models with Active Perception via GRPO—0
MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection—0
Application of YOLOv8 in monocular downward multiple Car Target detection—0
Learning to Borrow Features for Improved Detection of Small Objects in Single-Shot Detectors—0
MASF-YOLO: An Improved YOLOv11 Network for Small Object Detection on Drone View—0
HMPE:HeatMap Embedding for Efficient Transformer-Based Small Object Detection—0
self-prompting analogical reasoning for uav object detectionCode2
Context in object detection: a systematic literature review—0
Small Object Detection: A Comprehensive Survey on Challenges, Techniques and Real-World Applications—0
YOLO-LLTS: Real-Time Low-Light Traffic Sign Detection via Prior-Guided Enhancement and Multi-Branch Feature Interaction—0
Multi-Point Positional Insertion Tuning for Small Object Detection—0
PanSR: An Object-Centric Mask Transformer for Panoptic SegmentationCode0
RemDet: Rethinking Efficient Model Design for UAV Object DetectionCode2
Analysis of Object Detection Models for Tiny Object in Satellite Imagery: A Dataset-Centric Approach—0
YOLOv5-Based Object Detection for Emergency Response in Aerial Imagery—0
Dynamic Attention and Bi-directional Fusion for Safety Helmet Wearing Detection—0
Interpretable Dynamic Graph Neural Networks for Small Occluded Object Detection and Tracking—0
SL-YOLO: A Stronger and Lighter Drone Target Detection Model—0
Interactive Image-Based Aphid Counting in Yellow Water Traps under Stirring Actions—0
Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature IntegrationCode1
LAM-YOLO: Drones-based Small Object Detection on Lighting-Occlusion Attention Mechanism YOLO—0
PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplanar MRI SlicesCode1
Self-Supervised Learning for Real-World Object Detection: a Survey—0
Robust infrared small target detection using self-supervised and a contrario paradigms—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
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