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Pedestrian Detection

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하위 태스크: 1
평가표: 9
보존된 평가 기록: 92

Pedestrian detection is the task of detecting pedestrians from a camera.

Further state-of-the-art results (e.g. on the KITTI dataset) can be found at 3D Object Detection.

<span style="color:grey; opacity: 0.6">( Image credit: High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection )</span>

코드

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

https://github.com/GangmingZhao/GraphFPN-Graph-Feature-Pyramid-Network-for-Object-Detection

Focal Loss for Dense Object Detection

https://github.com/GianRomani/YOLOv3-Neural-Networks-project-

YOLOv3: An Incremental Improvement

https://github.com/GiantPandaCV/yolov3-point

YOLOv3: An Incremental Improvement

https://github.com/GiulioFischietti/Tirocinio

YOLOv3: An Incremental Improvement

https://github.com/GodofCCode/yolo3

YOLOv3: An Incremental Improvement

https://github.com/Guillem96/efficient-net-tf

Focal Loss for Dense Object Detection

https://github.com/Guillem96/efficientdet-tf

Focal Loss for Dense Object Detection

https://github.com/GunjanChourasia/custom_detector_yolov3

YOLOv3: An Incremental Improvement

https://github.com/GuoLiuFang/maskrcnn-benchmark-lfs

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/HRNet/HRNet-FCOS

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/HSRW-EMRP-WS1920-Drone/object_detection_and_landing

YOLOv3: An Incremental Improvement

https://github.com/Hernandope/keras_resnet_FPN_cifar10

Feature Pyramid Networks for Object Detection

https://github.com/Hiwyl/yolov3-attentation

YOLOv3: An Incremental Improvement

https://github.com/HongSic/DarknetAI

Focal Loss for Dense Object Detection

https://github.com/Hrishkesh/YoloInvoiceExtraction

YOLOv3: An Incremental Improvement

https://github.com/IPLI/IPLI_Server

Focal Loss for Dense Object Detection

https://github.com/Iamal1/maskrcnn-benchmark

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/IlyaOvodov/AngelinaReader

Focal Loss for Dense Object Detection

https://github.com/Information-Fusion-Lab-Umass/Salient-Pedestrian-Detection

Pedestrian Detection in Thermal Images using Saliency Maps

https://github.com/Iqbal1282/yolov3_incremental_distillation_loss

YOLOv3: An Incremental Improvement

https://github.com/JCamERG/YOLOPersonal

YOLOv3: An Incremental Improvement

https://github.com/JEONGHA-SHIN/YOGO_Server_v2

YOLOv3: An Incremental Improvement

https://github.com/JWMON/yolo

YOLOv3: An Incremental Improvement

https://github.com/Jamie725/Multimodal-Object-Detection-via-Probabilistic-Ensembling

Multimodal Object Detection via Probabilistic Ensembling

https://github.com/JaryHuang/awesome_SSD_FPN_GIoU

Feature Pyramid Networks for Object Detection

https://github.com/Jiachenyin1/Yolov3-U-attention-permuting

YOLOv3: An Incremental Improvement

https://github.com/Jintao-Huang/Darknet53_PyTorch

YOLOv3: An Incremental Improvement

https://github.com/Jo-dsa/SemanticSeg

Focal Loss for Dense Object Detection

https://github.com/Jonydom/Faster-RCNN

Feature Pyramid Networks for Object Detection

https://github.com/Jorge-Mendes/darknet-google-colab

YOLOv3: An Incremental Improvement

https://github.com/JunaidCS032/MOTBeyondPixels

Accurate Single Stage Detector Using Recurrent Rolling Convolution

https://github.com/KaiyangZhou/deep-person-reid

The P-DESTRE: A Fully Annotated Dataset for Pedestrian Detection, Tracking, Re-Identification and Search from Aerial Devices

https://github.com/Kenneth-Wong/tf-faster-rcnn

Feature Pyramid Networks for Object Detection

https://github.com/Keshavkant/YOLO_Toll

YOLOv3: An Incremental Improvement

https://github.com/Kev1nZheng/yolov_mask

YOLOv3: An Incremental Improvement

https://github.com/KingBoyBIT/yolov3test

Focal Loss for Dense Object Detection

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