Papers with Code 아카이브

3D Face Modelling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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코드

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

https://github.com/ifestus/rl

Proximal Policy Optimization Algorithms

https://github.com/iiTzFrankie/DCJT

https://github.com/iigroup/mm-celeba-hq-dataset

TediGAN: Text-Guided Diverse Face Image Generation and Manipulation

https://github.com/iitmcvg/Demo-of-face-detection-and-counting-

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/ikostrikov/cql-results

Conservative Q-Learning for Offline Reinforcement Learning

https://github.com/ikostrikov/jax-rl

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

https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail

Proximal Policy Optimization Algorithms

https://github.com/ikostrikov/pytorch-rl

Continuous Deep Q-Learning with Model-based Acceleration

https://github.com/ikostrikov/rlpd

Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations

https://github.com/ililily/retinaface

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/illidanlab/sail

Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations

https://github.com/imanlab/deep_movement_primitives

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/imkoushik22/Walmart-Hackathon

Deep Residual Learning for Image Recognition

https://github.com/immuno121/audio_source_classification

Sampling Matters in Deep Embedding Learning

https://github.com/in1t3r/ARS

Simple random search provides a competitive approach to reinforcement learning

https://github.com/inoryy/reaver

Proximal Policy Optimization Algorithms

https://github.com/intelligent-environments-lab/CityLearn

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/intellisys-lab/stellaris-sc24

Proximal Policy Optimization Algorithms

https://github.com/interdigitalinc/featurestyleencoder

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

https://github.com/interestingzhuo/foodretreival

Deep Residual Learning for Image Recognition

https://github.com/irom-princeton/dppo

Diffusion Policy Policy Optimization

https://github.com/irynakostyshyn/A-Style-Based-Generator-Architecture-for-GAN

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

https://github.com/isaacschaal/SG_training

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/isheunesutembo/TB-Computer-Aided-Diagnosis-Using-Deep-Learning

Deep Residual Learning for Image Recognition

https://github.com/ishspsy/project

Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape Models

https://github.com/iskandari/darknet

Focal Loss for Dense Object Detection

https://github.com/istvanmegyeri/audio_tagging

Focal Loss for Dense Object Detection

https://github.com/itanish/Face-Recognition

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/itijyou/ademxapp

Deep Residual Learning for Image Recognition

https://github.com/itsuki8914/ESRGAN-TensorFlow

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/ivanwilliammd/I3DR-Net-Transfer-Learning

Focal Loss for Dense Object Detection

https://github.com/ivclab/PAE

https://github.com/ivclab/agegenderLMTCNN

Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications

https://github.com/ivclab/cvs

Towards Backward-Compatible Representation Learning

https://github.com/ivychill/insightface

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/iwasakishuto/DeepScreening

FaceNet: A Unified Embedding for Face Recognition and Clustering

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