Papers with Code 아카이브

Object

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Replace the cat with a British Shorthair cat of the breed with bulging yellow eyes

코드

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

https://github.com/wangkingkingking/ssd_mathocr

SSD: Single Shot MultiBox Detector

https://github.com/wanglaotou/centernet_ncnn

Objects as Points

https://github.com/wangrui1996/caffe-ssd

SSD: Single Shot MultiBox Detector

https://github.com/wangxianhao/Improved-YOLOv3-for-UAV

Focal Loss for Dense Object Detection

https://github.com/wangxiao5791509/DeepMTA_PyTorch

Tracking Holistic Object Representations

https://github.com/wangxiao5791509/cmSalGAN_PyTorch

\emph{cm}SalGAN: RGB-D Salient Object Detection with Cross-View Generative Adversarial Networks

https://github.com/wangzpeng/tf-faster-rcnn

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

https://github.com/waspinator/deep-learning-explorer

https://github.com/watarus0208/ssd_keras

SSD: Single Shot MultiBox Detector

https://github.com/wavce/efficientdet-tf2

EfficientDet: Scalable and Efficient Object Detection

https://github.com/wayne1204/NOAA-fish-finding

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

https://github.com/wdlctc/darknet

YOLO9000: Better, Faster, Stronger

https://github.com/wecacuee/articulated-slam

Learning Articulated Motions From Visual Demonstration

https://github.com/weidalin/yolov4_mixup

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/weidi1024/caffe-ssd-correct

SSD: Single Shot MultiBox Detector

https://github.com/weijianan1/logichoi

Neural-Logic Human-Object Interaction Detection

https://github.com/wenbowen123/BundleTrack

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

https://github.com/wennieWN/endernewton_tf-faster-rcnn

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

https://github.com/wenquanlu/handrefiner

SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model

https://github.com/wentao99/pix2pixHD

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

https://github.com/wenyuqing/panacea

Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection

https://github.com/westerndigitalcorporation/YOLOv3-in-PyTorch

You Only Look Once: Unified, Real-Time Object Detection

https://github.com/wiegehtki/nvjetson_opencv_gsi

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/wiegehtki/zoneminder

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/wiegehtki/zoneminder-jetson

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/willT97/Zero-shot-Image-Captioner

Captioning Images with Diverse Objects

https://github.com/williamccondori/YOLO-NFPA

YOLO9000: Better, Faster, Stronger

https://github.com/wincelinux/ai-dn-FasterRCNN-caffe

R-FCN: Object Detection via Region-based Fully Convolutional Networks

https://github.com/witnessai/Awesome-Zero-Shot-Object-Detection

Polarity Loss for Zero-shot Object Detection

https://github.com/wittmaan/a2d2

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/witwickey/alexeyDarknet

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/witwickey/darknet

YOLO9000: Better, Faster, Stronger

https://github.com/wj1tr0y/SSD

SSD: Single Shot MultiBox Detector

https://github.com/wjy199708/my_point_painting

PointPainting: Sequential Fusion for 3D Object Detection

https://github.com/wk738126046/deploy

SSD: Single Shot MultiBox Detector

https://github.com/wodyjowski/colab-training

YOLO9000: Better, Faster, Stronger

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