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/hggym/pigo

Object Detection with Pixel Intensity Comparisons Organized in Decision Trees

https://github.com/hh-xiaohu/Image-augementation-pytorch

Training Region-based Object Detectors with Online Hard Example Mining

https://github.com/hhenryd/tap

Learning to Prompt for Vision-Language Models

https://github.com/hhj1897/face_detection

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/hhuaibo/darknet

Focal Loss for Dense Object Detection

https://github.com/hieu2906090/deep-learning-in-js

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hill-a/stable-baselines

Continuous control with deep reinforcement learning

https://github.com/hisiter97/darknet

Focal Loss for Dense Object Detection

https://github.com/hmhuy0/SIM-RL

Proximal Policy Optimization Algorithms

https://github.com/hnVfly/pointnet.mxnet

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

https://github.com/hnmspirit/pointnet1

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

https://github.com/hollance/BlazeFace-PyTorch

BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs

https://github.com/hollance/VGGNet-Metal

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/holman57/AI_Emotion_Detection

Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution

https://github.com/holstgr-kaust/keras-tutorials

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hongkunsun/paratranscnn

Deep Residual Learning for Image Recognition

https://github.com/hongyi-zhang/Fixup

Deep Residual Learning for Image Recognition

https://github.com/horizontel/aigibench

Generalizable Deepfake Detection via Effective Local-Global Feature Extraction

https://github.com/horse007666/ResNet

Deep Residual Learning for Image Recognition

https://github.com/hqhoangvuong/paperspace_ml_01

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/hqli/face_recognition

DeepID3: Face Recognition with Very Deep Neural Networks

https://github.com/hqng/imm-pytorch

Unsupervised Learning of Object Landmarks through Conditional Image Generation

https://github.com/hsd1503/resnet1d

Deep Residual Learning for Image Recognition

https://github.com/hsgrandhi/AIProject

World Models

https://github.com/hsinyilin19/resnetvae

Deep Residual Learning for Image Recognition

https://github.com/hslrock/TripletLoss_Pytorch

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/huangshenneng/padd_retinaface

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/huanzhang12/sa_ppo

Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

https://github.com/huashen218/multiturncleanup

Does Human Collaboration Enhance the Accuracy of Identifying LLM-Generated Deepfake Texts?

https://github.com/huawenwei4/dfl

DeepFaceLab: Integrated, flexible and extensible face-swapping framework

https://github.com/hubert0527/COCO-GAN

COCO-GAN: Generation by Parts via Conditional Coordinating

https://github.com/hui-po-wang/hijackgan

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

https://github.com/hukangli/https-github.com-deepinsight-insightface

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/hukkelas/DSFD-Pytorch-Inference

DSFD: Dual Shot Face Detector

https://github.com/hukkelas/progan-pytorch

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

https://github.com/human-analysis/RankGAN

RankGAN: A Maximum Margin Ranking GAN for Generating Faces

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