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 101–125 of 152 papers

TitleStatusHype
Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects—0
Dr2Net: Dynamic Reversible Dual-Residual Networks for Memory-Efficient Finetuning—0
Dynamic Attention and Bi-directional Fusion for Safety Helmet Wearing Detection—0
Dynamic Tiling: A Model-Agnostic, Adaptive, Scalable, and Inference-Data-Centric Approach for Efficient and Accurate Small Object Detection—0
Enhanced Single-shot Detector for Small Object Detection in Remote Sensing Images—0
Enhancing Lightweight Neural Networks for Small Object Detection in IoT Applications—0
Enhancing Object Detection with Hybrid dataset in Manufacturing Environments: Comparing Federated Learning to Conventional Techniques—0
Ensemble Fusion for Small Object Detection—0
Evaluation of YOLO Models with Sliced Inference for Small Object Detection—0
Fast Fourier Convolution Based Remote Sensor Image Object Detection for Earth Observation—0
Focus-and-Detect: A Small Object Detection Framework for Aerial Images—0
High-order Spatial Interactions Enhanced Lightweight Model for Optical Remote Sensing Image-based Small Ship Detection—0
HMPE:HeatMap Embedding for Efficient Transformer-Based Small Object Detection—0
HRDNet: High-resolution Detection Network for Small Objects—0
Progressive Domain Adaptation with Contrastive Learning for Object Detection in the Satellite Imagery—0
Infra-YOLO: Efficient Neural Network Structure with Model Compression for Real-Time Infrared Small Object Detection—0
Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks—0
Interactive Image-Based Aphid Counting in Yellow Water Traps under Stirring Actions—0
Intrinsic Relationship Reasoning for Small Object Detection—0
IPG-Net: Image Pyramid Guidance Network for Small Object Detection—0
iSmallNet: Densely Nested Network with Label Decoupling for Infrared Small Target Detection—0
Joint-YODNet: A Light-weight Object Detector for UAVs to Achieve Above 100fps—0
Feature Selective Small Object Detection via Knowledge-based Recurrent Attentive Neural Network—0
Small traffic sign detection from large image—0
SOAR: Advancements in Small Body Object Detection for Aerial Imagery Using State Space Models and Programmable Gradients—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