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

2

보존된 평가 기록

3

코드

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

https://github.com/tamerthamoqa/facenet-pytorch-glint360k

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/tamnil/esp32-xtensa-study

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

https://github.com/taniokah/liarr2017

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/tanjeffreyz/deep-residual-learning

Deep Residual Learning for Image Recognition

https://github.com/tanmaysingha/2D-3D-FAN

How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)

https://github.com/taotaonice/FaceShifter

FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping

https://github.com/tarod13/SAC

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

https://github.com/tarun-98/COMP8240_Project_GroupG

Facial Motion Prior Networks for Facial Expression Recognition

https://github.com/tatsu-lab/linguistic_calibration

Proximal Policy Optimization Algorithms

https://github.com/taufikxu/youtube

YouTube-8M: A Large-Scale Video Classification Benchmark

https://github.com/taylorlu/ghostvlad-speaker

GhostVLAD for set-based face recognition

https://github.com/tbmoon/facenet

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/tcheung99/ResNet_MiniProject

Deep Residual Learning for Image Recognition

https://github.com/tcmxx/CNTKUnityTools

Proximal Policy Optimization Algorithms

https://github.com/teemoeric/projet

Focal Loss for Dense Object Detection

https://github.com/tegg89/DLCamp_Jeju2018

Continuous control with deep reinforcement learning

https://github.com/tegg89/magnet

Continuous control with deep reinforcement learning

https://github.com/tegg89/magnn

Continuous control with deep reinforcement learning

https://github.com/tegg89/mann

Continuous control with deep reinforcement learning

https://github.com/tegg89/paper-notes

World Models

https://github.com/tejaswigowda/semseg-pytorch

High-Resolution Representations for Labeling Pixels and Regions

https://github.com/tencentarc/opencompatible

Towards Universal Backward-Compatible Representation Learning

https://github.com/tensorflow/models/tree/master/research/audioset

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/tensorflow/models/tree/master/research/deep_contextual_bandits

Parameter Space Noise for Exploration

https://github.com/tensorflow/models/tree/master/research/deeplab

Deep Residual Learning for Image Recognition

https://github.com/tensorflow/models/tree/master/research/efficient-hrl

Near-Optimal Representation Learning for Hierarchical Reinforcement Learning

https://github.com/tensorflow/models/tree/master/research/slim

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/tensorlayer/RLzoo

Continuous control with deep reinforcement learning

https://github.com/tensorpack/tensorpack

Deep Residual Learning for Image Recognition

https://github.com/tensorpack/tensorpack/tree/master/examples/ResNet

Deep Residual Learning for Image Recognition

https://github.com/text-machine-lab/transformerpy

A Structured Self-attentive Sentence Embedding

https://github.com/textvec/textvec

Inverse-Category-Frequency based supervised term weighting scheme for text categorization

https://github.com/tg-bomze/Face-Depixelizer

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

https://github.com/tgeorgy/mgan

GANimation: Anatomically-aware Facial Animation from a Single Image

https://github.com/thainv0212/re-ddpg

Continuous control with deep reinforcement learning

https://github.com/thanhhungqb/pyramid-super-resolution

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