Papers with Code 아카이브

2D Classification

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전체 기법전체 데이터셋

하위 태스크

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보존된 평가 기록

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코드

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

https://github.com/Yang-YiFan/DiracDeltaNet

SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

https://github.com/Yang2446/pointnet

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

https://github.com/Yanghojun/Custom_yolov5_pytorch

StrongSORT: Make DeepSORT Great Again

https://github.com/YangtaoWANG95/TokenCut

Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut

https://github.com/YapengTian/TDAN-VSR-CVPR-2020

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

https://github.com/Yashgh7076/CU-Thesis

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Yashgh7076/Eluvio-ML-Scene-Segmentation

Focal Loss for Dense Object Detection

https://github.com/Yc174/frustum-pointnets

Frustum PointNets for 3D Object Detection from RGB-D Data

https://github.com/YeLyuUT/MMDET

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/YeLyuUT/VISLNet

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/YeongHyeon/ReXNet-TF2

Rethinking Channel Dimensions for Efficient Model Design

https://github.com/YeongHyeon/ResNeSt-TF2

ResNeSt: Split-Attention Networks

https://github.com/YerevaNN/SciERC

Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction

https://github.com/Yimin-Yuan/VeinProject

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/YinDFY/PGD_for_targeted_attack

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/Yingqiancui/FT-Shield

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models

https://github.com/YininKorea/Contour-aware-equipotential-learning

Pyramid Scene Parsing Network

https://github.com/YiruS/pointnet_adversarial

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

https://github.com/YiteWang/CS547-final-project

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/Yonder-OSS/D3M-Primitives

Focal Loss for Dense Object Detection

https://github.com/YongWookHa/swin-transformer-ocr

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

https://github.com/Yongjjun/singleshotpose

BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth

https://github.com/Yotonctu/densefusion_torch1.0

DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion

https://github.com/YouYueHuang/CycleGAN_Unsupervised_Domain_Adaptation

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/Yougunhee/cycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/YoungWoong-Cho/Decay

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/YoungXIAO13/FewShotDetection

Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild

https://github.com/YoungXIAO13/PoseContrast

Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild

https://github.com/YourGc/Unet_jinnan2

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/YoushaaMurhij/FasterCNN_Object_Detection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/YudeWang/UNet-Satellite-Image-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/YuefeiZ/PANet

Path Aggregation Network for Instance Segmentation

https://github.com/YuemingJin/TMRNet

EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

https://github.com/YufeiHU-fr/obow_ssl

OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning

https://github.com/YukangWang/DeepFlux

DeepFlux for Skeletons in the Wild

https://github.com/Yuma82/Paper-Survey

ODAM: Gradient-based instance-specific visual explanations for object detection

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