Papers with Code 아카이브

Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

39

평가표

124

보존된 평가 기록

977

코드

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

https://github.com/kukby/Mish-semantic-segmentation-pytorch

Pyramid Scene Parsing Network

https://github.com/kuku-sichuan/CenterNet

CenterNet: Keypoint Triplets for Object Detection

https://github.com/kun-g/Scraping-Github-trending

YOLOP: You Only Look Once for Panoptic Driving Perception

https://github.com/kun-woo-park/Deeplearning_project_STL_10

Deep Residual Learning for Image Recognition

https://github.com/kunglab/ddnn

Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges

https://github.com/kushaswani/LitterNet-webapp

EfficientDet: Scalable and Efficient Object Detection

https://github.com/kusti8/yolov3

YOLOv3: An Incremental Improvement

https://github.com/kvijaykrish/Bosch_AI_VehicleClassification

YOLO9000: Better, Faster, Stronger

https://github.com/kwantommy/SE-ResNeXt-image-classification

Squeeze-and-Excitation Networks

https://github.com/kwantommy/fgvc6-kaggle-cassava-classification

Deep Residual Learning for Image Recognition

https://github.com/kwcckw/unet_magnetic_tiles_defects

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kwotsin/TensorFlow-ENet

Deep Residual Learning for Image Recognition

https://github.com/kyegomez/PALI

PaLI-X: On Scaling up a Multilingual Vision and Language Model

https://github.com/kyip375/ScaledYOLOv4

Scaled-YOLOv4: Scaling Cross Stage Partial Network

https://github.com/kyle-dorman/bayesian-neural-network-blogpost

Deep Residual Learning for Image Recognition

https://github.com/kynkaat/role-of-imagenet-classes-in-fid

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/kyscg/tf-models

Mobile Video Object Detection with Temporally-Aware Feature Maps

https://github.com/kyunghwan/darknet_v3

YOLO9000: Better, Faster, Stronger

https://github.com/kyungsu-lee-ksl/ash

ImageNet Large Scale Visual Recognition Challenge

https://github.com/lRomul/argus-tgs-salt

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/lab-midas/med_segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/labmlai/annotated_deep_learning_paper_implementations

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/lachinov/brats2018-graphlabunn

Glioma Segmentation with Cascaded Unet

https://github.com/laclouis5/darknet2

YOLOv3: An Incremental Improvement

https://github.com/lampsonSong/tinySSD

Tiny SSD: A Tiny Single-shot Detection Deep Convolutional Neural Network for Real-time Embedded Object Detection

https://github.com/lanPN85/HarDNet-MSEG

HarDNet: A Low Memory Traffic Network

https://github.com/landskape-ai/triplet-attention

Rotate to Attend: Convolutional Triplet Attention Module

https://github.com/lanmei1211/face

YOLOv3: An Incremental Improvement

https://github.com/laobaiswag/openpose1

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/laowang666888/HRNET

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/lartpang/CMWNet.pytorch

Cross-Modal Weighting Network for RGB-D Salient Object Detection

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

RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

https://github.com/laugh12321/3D-Attention-Keras

CBAM: Convolutional Block Attention Module

https://github.com/lavender105/rsgpt

Vision-Language Models in Remote Sensing: Current Progress and Future Trends

https://github.com/laxmichary/Pytorch-UNet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/laycoding/FaceDetection

Single-Shot Refinement Neural Network for Object Detection

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