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 126–150 of 152 papers

TitleStatusHype
Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss—0
Robust Small Object Detection on the Water Surface Through Fusion of Camera and Millimeter Wave Radar—0
SWIPENET: Object detection in noisy underwater images—0
Mind the Pad -- CNNs can Develop Blind SpotsCode0
Intrinsic Relationship Reasoning for Small Object Detection—0
1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection TrackCode0
HRDNet: High-resolution Detection Network for Small Objects—0
MultiResolution Attention Extractor for Small Object Detection—0
Underwater object detection using Invert Multi-Class Adaboost with deep learning—0
Spatio-temporal Tubelet Feature Aggregation and Object Linking in Videos—0
Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology—0
DeepSperm: A robust and real-time bull sperm-cell detection in densely populated semen videos—0
Small Object Detection using Context and Attention—0
IPG-Net: Image Pyramid Guidance Network for Small Object Detection—0
Better to Follow, Follow to Be Better: Towards Precise Supervision of Feature Super-Resolution for Small Object Detection—0
Small traffic sign detection from large image—0
The Power of Tiling for Small Object Detection—0
Multiple receptive fields and small-object-focusing weakly-supervised segmentation network for fast object detection—0
SOD-MTGAN: Small Object Detection via Multi-Task Generative Adversarial Network—0
MITOS-RCNN: A Novel Approach to Mitotic Figure Detection in Breast Cancer Histopathology Images using Region Based Convolutional Neural Networks—0
MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small ObjectsCode0
Feature Selective Small Object Detection via Knowledge-based Recurrent Attentive Neural Network—0
3D Regression Neural Network for the Quantification of Enlarged Perivascular Spaces in Brain MRI—0
Feature-Fused SSD: Fast Detection for Small ObjectsCode0
Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects—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