Small Object Detection
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Benchmarks
Most implemented
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection
Augmentation for small object detection
Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network
Small Object Detection via Pixel Level Balancing With Applications to Blood Cell Detection
A Normalized Gaussian Wasserstein Distance for Tiny Object Detection
Papers
ScopeMamba-YOLO: Widening the Perceptual Scope Inward and Outward for Small Object Detection in Remote Sensing Imagery
Small object detection in unmanned aerial vehicle (UAV) and remote sensing imagery requires preserving high-resolution detail while modeling long-range context. Adding a stride-4 detection level and removing the stride-3…
Small Object DetectionMetric-Guided Synthetic Image Data Rendering for Deep Learning compatible with Agentic AI
Deep learning computer vision for scientific applications requires collecting and annotating large datasets in a laborious, expensive and error-prone process. Synthetic data generation through 3D modelling and rendering …
Synthetic Data GenerationSmall Object DetectionFSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection
Small object detection (SOD) remains a challenging task in real-world applications. Despite recent advances, existing detectors remain limited by rigid processing that entangle spatial aggregation with implicit frequency…
Small Object DetectionFRFDet: Efficient UAV Small Object Detection with Symmetric Sampling and Scalable Fusion
Small object detection in Unmanned Aerial Vehicle (UAV) imagery remains challenging under adverse conditions, including complex weather, low illumination, and sensor noise. These challenges mainly stem from severe backgr…
Small Object DetectionAdaptive Spectrum-Aware Feature Disentangled Network for Small Object Detection
Small Object Detection (SOD) is a fundamental yet challenging problem in computer vision due to its limited spatial resolution and weak visual cues. Although recent approaches have achieved remarkable advances, the backg…
Small Object DetectionFrom Spatial to Spectral: An Efficient, Frequency-Guided Feature Representation Learner for Small Object Detection
Efficient small object detection is bottlenecked by the inherent feature scarcity of tiny targets, which is further aggravated by operations of spatial-domain detectors that indiscriminately discard critical high-frequen…
Small Object Detection