Papers with Code 아카이브

2D Classification

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전체 기법전체 데이터셋

하위 태스크

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코드

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

https://github.com/ThomasEhling/Weight_Standardization

Micro-Batch Training with Batch-Channel Normalization and Weight Standardization

https://github.com/ThomasGoerttler/similarity-analysis-of-maml

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/TiagoCortinhal/SalsaNext

Deep Learning for 3D Point Clouds: A Survey

https://github.com/Tiannia/intro_to_ai

A Neural Algorithm of Artistic Style

https://github.com/TiantianWang/ICCV17_SRM

https://github.com/TianxiangMa/MUST-GAN

MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generation

https://github.com/Tianxiaomo/pytorch-YOLOv4

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/TianyiZhang0315/CV_FinalProject

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/Tikquuss/meta_XLM

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/TimDettmers/transformer-xl

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

https://github.com/TimVerion/caffe_rfcn

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

https://github.com/Tirth27/Skin-Cancer-Classification-using-Deep-Learning

Bag of Tricks for Image Classification with Convolutional Neural Networks

https://github.com/TobiasGruening/ARU-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/TongUI-agent/TongUI-agent

TongUI: Building Generalized GUI Agents by Learning from Multimodal Web Tutorials

https://github.com/Tony363/Teamplay_Yolov3

YOLOv3: An Incremental Improvement

https://github.com/Tony607/mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/TonyRays/U-net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/TonyYaoMSU/ProjectedGradientDescent

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/Tonyhuiii/color-transform

A Style-Aware Content Loss for Real-time HD Style Transfer

https://github.com/TooTouch/WhiteBox-Part1

CBAM: Convolutional Block Attention Module

https://github.com/ToposInstitute/tac-corpus

Parmesan: mathematical concept extraction for education

https://github.com/Tota-Nakatani/SSD_keras

SSD: Single Shot MultiBox Detector

https://github.com/TotoHugo/facedetection-lite-Outsystems

Object Detection with Pixel Intensity Comparisons Organized in Decision Trees

https://github.com/Totraproducts/AerialObjectDetection

Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges

https://github.com/TowardHumanizedInteraction/TripletFace

Deep Residual Learning for Image Recognition

https://github.com/Traffic-X/MonoUNI

https://github.com/Traffic-X/ViT-CoMer

https://github.com/TranThienDat-Nguyen/VisionEvaluation

How Trustworthy are Performance Evaluations for Basic Vision Tasks?

https://github.com/TravisLeeTS/grabcvchallenge

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/TravisTorch/Pytorch

YOLOv3: An Incremental Improvement

https://github.com/TristansCloud/YellowstonesVegitiation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/TrustAI/DeepConcolic

Embedding and Extraction of Knowledge in Tree Ensemble Classifiers

https://github.com/Trustworthy-AI-Group/TransferAttack

Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer

https://github.com/Tsejing/object_detection

SSD: Single Shot MultiBox Detector

https://github.com/Tu-kun/cultivated_landdivision

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/TuSimple/RangeDet

Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection

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