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/rbgirshick/DeepPyramid

Deformable Part Models are Convolutional Neural Networks

https://github.com/rbgirshick/rcnn

Rich feature hierarchies for accurate object detection and semantic segmentation

https://github.com/rdadlaney/Audio-Denoiser-CNN

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/realdingke/mscai_softwareengineering_project

FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking

https://github.com/realmichaelye/Skin-Lesions-Classifier-ResNet50

Deep Residual Learning for Image Recognition

https://github.com/rebeccagio/object_detection

Focal Loss for Dense Object Detection

https://github.com/rechardchen123/YOLOv4_traffic_sign_detection

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/redcaps-dataset/redcaps-downloader

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/redwankarimsony/darknet-yolov4-working

YOLOv3: An Incremental Improvement

https://github.com/reenal/melanoma-skin-cancer-image-segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/refkxh/DUSA

CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers

https://github.com/remydubois/lsnms

Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection

https://github.com/renhaa/semantic-diffusion

BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

https://github.com/renmada/MnasNet-paddle

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/researchmm/SiamDW

Going Deeper with Convolutions

https://github.com/researchmm/WSOD2

Weakly Supervised Deep Detection Networks

https://github.com/retis-ai/semsegadvpatch

Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks

https://github.com/revbucket/mister_ed

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/revsic/tf-mlptts

CycleMLP: A MLP-like Architecture for Dense Prediction

https://github.com/reyvaz/pneumothorax_detection

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/reyvaz/steel-defect-segmentation

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/rezazad68/BCDU-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/rfribeiro/face_detection

SSD: Single Shot MultiBox Detector

https://github.com/rfribeiro/face_detection_landmarks

SSD: Single Shot MultiBox Detector

https://github.com/rgeirhos/texture-vs-shape

ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

https://github.com/rh01/fast-rnn

Fast R-CNN

https://github.com/rh01/faster-rcnn

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

https://github.com/rhllasag/SLIMYoloV3

SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications

https://github.com/richardaecn/cvpr18-inaturalist-transfer

Squeeze-and-Excitation Networks

https://github.com/richmondvan/melanoma-detection

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/ricky40403/Fcos_seg

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/rickyHong/DeepOcclustion-repl

Deep Occlusion Reasoning for Multi-Camera Multi-Target Detection

https://github.com/rickyHong/FPN-repl

Feature Pyramid Networks for Object Detection

https://github.com/rickyHong/Random-erasing-Data-Augumentation-repl

Random Erasing Data Augmentation

https://github.com/rickyHong/UNet-segmentation-pytorch-repl

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/rickyHong/faster-rcnn-tensorflow-repl

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

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