Papers with Code 아카이브

3D Face Modelling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

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평가표

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보존된 평가 기록

3

코드

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

https://github.com/buptdbj/darknet-windows-linux

Focal Loss for Dense Object Detection

https://github.com/busyboxs/Some-resources-useful-for-me

Training Region-based Object Detectors with Online Hard Example Mining

https://github.com/bxz9200/ultraclean

Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

https://github.com/c1ph3rr/Deep-Residual-Learning-for-Image-Recognition

Deep Residual Learning for Image Recognition

https://github.com/c1ph3rr/Very-Deep-Convolutional-Networks-For-Large-Scale-Image-Recognition

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/caihaocong/Yolov3_AlexeyAB_Version

Focal Loss for Dense Object Detection

https://github.com/caihuaiguang/CHG-Shapley-for-Data-Selection

Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision

https://github.com/calmisential/TensorFlow2.0_Image_Classification

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/calmisential/TensorFlow2.0_ResNet

Deep Residual Learning for Image Recognition

https://github.com/camall3n/atari-MAC

Mean Actor Critic

https://github.com/camel007/caffe-moon

MOON: A Mixed Objective Optimization Network for the Recognition of Facial Attributes

https://github.com/cameronchoi/r3det-copy

Deep Residual Learning for Image Recognition

https://github.com/canturan10/light_side

Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement

https://github.com/canturan10/satellighte

Deep Residual Learning for Image Recognition

https://github.com/caojoshua/Plastic-Recyclability

Deep Residual Learning for Image Recognition

https://github.com/cardwing/Codes-for-Steering-Control

Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks

https://github.com/carlosb1/upc-aidl-19-team4

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/carolgithubv1/convnets-keras

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/cat-claws/RobFace

FaceX-Zoo: A PyTorch Toolbox for Face Recognition

https://github.com/cataluna84/WorldModels_v1.0

World Models

https://github.com/catalyst-team/catalyst-rl-framework

Catalyst.RL: A Distributed Framework for Reproducible RL Research

https://github.com/cathywu/rllab-multiagent

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/cav-research-lab/predictive-model-delay-correction

Reinforcement Learning with Random Delays

https://github.com/cbfinn/maml_rl

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/cc-hpc-itwm/DeepFakeDetection

Progressive Growing of GANs for Improved Quality, Stability, and Variation

https://github.com/cchinchristopherj/Right-Whale-Unsupervised-Model

Network In Network

https://github.com/ccolas/rl_stats

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/cecile-hi/regularized-adaptive-weight-modification

What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection

https://github.com/cedricoeldorf/ConditionalStyleGAN

Progressive Growing of GANs for Improved Quality, Stability, and Variation

https://github.com/celsolbm/Attention_Text

A Structured Self-attentive Sentence Embedding

https://github.com/celsolbm/imdb_sentiment_experiments

A Structured Self-attentive Sentence Embedding

https://github.com/cem8301/EmotionDetector

Deep Facial Expression Recognition: A Survey

https://github.com/cfl0122/face

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/chainer/chainerrl

Continuous control with deep reinforcement learning

https://github.com/chamikara1986/BA-BAM

Resurrecting Trust in Facial Recognition: Mitigating Backdoor Attacks in Face Recognition to Prevent Potential Privacy Breaches

https://github.com/chamorajg/pl-dreamer

Dream to Control: Learning Behaviors by Latent Imagination

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