Papers with Code 아카이브

3D Face Modelling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

2

평가표

2

보존된 평가 기록

3

코드

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

https://github.com/gwthomas/gtml

Continuous control with deep reinforcement learning

https://github.com/gyes00205/waymo_tf_object_detection

Focal Loss for Dense Object Detection

https://github.com/h-aboutalebi/SparceReward

Continuous control with deep reinforcement learning

https://github.com/haaz77/keras-tutorials

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/haithink/myWindowsDarknet

Focal Loss for Dense Object Detection

https://github.com/hakaneroztekin/face-recognition

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/halajadallah/RL-Quadcopter_project

Continuous control with deep reinforcement learning

https://github.com/hamidthri/navbot_ppo

Virtual-to-real Deep Reinforcement Learning: Continuous Control of Mobile Robots for Mapless Navigation

https://github.com/hamishs/JAX-RL

Continuous control with deep reinforcement learning

https://github.com/hamzaMahdi/darknet

Focal Loss for Dense Object Detection

https://github.com/hankpark0706/darknet

Focal Loss for Dense Object Detection

https://github.com/hantek/SelfAttentiveSentEmbed

A Structured Self-attentive Sentence Embedding

https://github.com/hao-qiang/GANimation-tf

GANimation: Anatomically-aware Facial Animation from a Single Image

https://github.com/haonanguo/remote-sensing-chatgpt

Deep Residual Learning for Image Recognition

https://github.com/haosulab/ManiSkill-Learn

Off-Policy Deep Reinforcement Learning without Exploration

https://github.com/happy-jihye/Cartoon-StyleGAN

Fine-Tuning StyleGAN2 For Cartoon Face Generation

https://github.com/hardik-uppal/CNN-fusion-networks

Two-Level Attention-based Fusion Learning for RGB-D Face Recognition

https://github.com/hardmaru/WorldModelsExperiments

World Models

https://github.com/hari-sikchi/loop

Learning Off-Policy with Online Planning

https://github.com/harruff/Senior_Project_Repository

Proximal Policy Optimization Algorithms

https://github.com/harunshimanto/Neural-Style-Transfer-of-Artistic-Style

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hashmatshadab/apr

Practical No-box Adversarial Attacks against DNNs

https://github.com/hazdzz/BGU

Predicting distributions with Linearizing Belief Networks

https://github.com/hcholab/k-salsa

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

https://github.com/hcygeorge/aoi_defect_detection

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hdilab/world_model_experiments

World Models

https://github.com/hdparks/AsteroidsDeepReinforcement

Proximal Policy Optimization Algorithms

https://github.com/healthx-lab/biomedcoop

Learning to Prompt for Vision-Language Models

https://github.com/heathentw/prnet-tf2

Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

https://github.com/hebowei2000/deep-reinforcement-learning

Near-Optimal Representation Learning for Hierarchical Reinforcement Learning

https://github.com/hectorgie/DeepFaceLab

DeepFaceLab: Integrated, flexible and extensible face-swapping framework

https://github.com/hemanshanand/Facial-Expression-Recognition

Challenges in Representation Learning: A report on three machine learning contests

https://github.com/hemilpanchiwala/Hindsight-Experience-Replay

Continuous control with deep reinforcement learning

https://github.com/henriquemeloo/cat-dog-image-classifier

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/heorhii-bolotov/facenet

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/hershd23/ObjectLocalizer

Deep Residual Learning for Image Recognition

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