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/mindspore-ai/contrib/tree/master/papers/Zero-DCE

Low-Light Image and Video Enhancement Using Deep Learning: A Survey

https://github.com/mindspore-ai/contrib/tree/master/papers/Zero-DCE%2B%2B

Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation

https://github.com/mindspore-ai/models/blob/master/official/cv/retinanet/

Focal Loss for Dense Object Detection

https://github.com/mindspore-ai/models/blob/master/research/cv/LightCNN/

A Light CNN for Deep Face Representation with Noisy Labels

https://github.com/mindspore-ai/models/blob/master/research/cv/PGAN/

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

https://github.com/mindspore-ai/models/blob/master/research/cv/retinaface

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/mindspore-ai/models/blob/master/research/cv/retinanet_resnet152

Focal Loss for Dense Object Detection

https://github.com/mindspore-ai/models/tree/master/official/cv/centerface

CenterFace: Joint Face Detection and Alignment Using Face as Point

https://github.com/mindspore-ai/models/tree/master/official/cv/resnet

Deep Residual Learning for Image Recognition

https://github.com/mindspore-ai/models/tree/master/official/cv/resnet50_quant

Deep Residual Learning for Image Recognition

https://github.com/mindspore-ai/models/tree/master/official/cv/resnet_thor

Deep Residual Learning for Image Recognition

https://github.com/mindspore-ai/models/tree/master/official/cv/retinaface_resnet50

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/mindspore-ai/models/tree/master/official/cv/sphereface

SphereFace: Deep Hypersphere Embedding for Face Recognition

https://github.com/mindspore-ai/models/tree/master/official/cv/vgg16

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/mindspore-ai/models/tree/master/research/cv/DeepID

https://github.com/mindspore-ai/models/tree/master/research/cv/ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/mindspore-ai/models/tree/master/research/cv/FaceAttribute

Deep Residual Learning for Image Recognition

https://github.com/mindspore-ai/models/tree/master/research/cv/HRNetW48_cls

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/mindspore-ai/models/tree/master/research/cv/PGAN

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

https://github.com/mindspore-ai/models/tree/master/research/cv/arcface

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/mindspore-ai/models/tree/master/research/cv/vgg19

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/mindspore-courses/Deep-Reinforcement-Learning-Algorithms-with-MindSpore

Continuous control with deep reinforcement learning

https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/backbone/resnet.py

Deep Residual Learning for Image Recognition

https://github.com/mindspore-courses/MindSpore-classification

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/mindspore-courses/heads-on-mindspore/tree/main/1-best-practice/models

Deep Residual Learning for Image Recognition

https://github.com/mindspore-ecosystem/mindcv/blob/main/mindcv/models/resnet.py

Deep Residual Learning for Image Recognition

https://github.com/mindspore-ecosystem/mindcv/blob/main/mindcv/models/vgg.py

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/mindspore-lab/mindone

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/mingxingtan/efficientnet

Deep Residual Learning for Image Recognition

https://github.com/minhdua/PHONES

Focal Loss for Dense Object Detection

https://github.com/minhncedutw/pointnet1_keras

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

https://github.com/minhphd/PyDreamerV1

Dream to Control: Learning Behaviors by Latent Imagination

https://github.com/minoring/PRNet

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

https://github.com/minoring/nin-tf2

Network In Network

https://github.com/minus31/BlazeFace

BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs

https://github.com/minzwon/tag-based-music-retrieval

Sampling Matters in Deep Embedding Learning

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