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Small Object Detection

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하위 태스크: 1
평가표: 4
보존된 평가 기록: 12

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.

<span style="color:grey; opacity: 0.6">( Image credit: Feature-Fused SSD )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/shaunyuan22/cfinet

공식 코드

Small Object Detection via Coarse-to-fine Proposal Generation and Imitation Learning

https://github.com/shinya7y/UniverseNet

공식 코드

BandRe: Rethinking Band-Pass Filters for Scale-Wise Object Detection Evaluation

https://github.com/sinatayebati/radial_mae

공식 코드

Sense Less, Generate More: Pre-training LiDAR Perception with Masked Autoencoders for Ultra-Efficient 3D Sensing

https://github.com/tchittesh/fovea

공식 코드

FOVEA: Foveated Image Magnification for Autonomous Navigation

https://github.com/wcyjerry/UCFnet

공식 코드

Local Contrast and Global Contextual Information Make Infrared Small Object Salient Again

https://github.com/wcyjerry/basicisos

공식 코드

Local Contrast and Global Contextual Information Make Infrared Small Object Salient Again

https://github.com/wnzhyee/Feature-Fused-SSD

공식 코드

Feature-Fused SSD: Fast Detection for Small Objects

https://github.com/xuxw98/dspdet3d

공식 코드

3D Small Object Detection with Dynamic Spatial Pruning

https://github.com/yangxue0827/RotationDetection

공식 코드

Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss

https://github.com/zhengshuchen/hcfnet

공식 코드

HCF-Net: Hierarchical Context Fusion Network for Infrared Small Object Detection

https://github.com/ziyueqingwan/localglobalattention

공식 코드

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration

https://github.com/zk2172-columbia/constellation-dataset

공식 코드

Constellation Dataset: Benchmarking High-Altitude Object Detection for an Urban Intersection

https://github.com/2024-MindSpore-1/Code3/tree/main/ResNet18

Augmentation for small object detection

https://github.com/2anchao/VovJpu

An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection

https://github.com/6QHTSK/paper-database

Mind the Pad -- CNNs can Develop Blind Spots

https://github.com/Dandelight/VoVNet-PaddlePaddle

An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection

https://github.com/Jakaria08/EESRGAN

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

https://github.com/Jakaria08/F-EESRGAN

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

https://github.com/Kazuhito00/sahi-yolox-onnx-sample

Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection

https://github.com/NaCl-Ocean/Anchor_free_detection_rotation

1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track

https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/smalldet

Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection

https://github.com/Resham-Sundar/sahi-yolox

Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection

https://github.com/airctic/icevision

Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection

https://github.com/bhyun-kim/NWD

A Normalized Gaussian Wasserstein Distance for Tiny Object Detection

https://github.com/delixing/Data-Augmentation

Augmentation for small object detection

https://github.com/divyam96/EESRGAN

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

https://github.com/finepix/small_object_augmentation

Augmentation for small object detection

https://github.com/gene-chou/EFPN-detectron2

Extended Feature Pyramid Network for Small Object Detection

https://github.com/neilctwu/FCOS-pytorch_Simplified

An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection

https://github.com/nqt228/YoloZ

YOLO-Z: Improving small object detection in YOLOv5 for autonomous vehicles

https://github.com/open-mmlab/mmrotate

Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss

https://github.com/osmr/imgclsmob

An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection

https://github.com/pierlj/pycocosiou

A Normalized Gaussian Wasserstein Distance for Tiny Object Detection

https://github.com/siddhanthaldar/PyTorch_Object_Detection

MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small Objects

https://github.com/stigma0617/VoVNet-DeepLabV3

An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection

https://github.com/stigma0617/VoVNet.pytorch

An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.