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평가표

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보존된 평가 기록

1

코드

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

https://github.com/bmy4415/DMLAB-intern

Show and Tell: A Neural Image Caption Generator

https://github.com/bnestor/second-hand-rl

Learning to Estimate 3D Hand Pose from Single RGB Images

https://github.com/bo-zhang-cs/CACNet-Pytorch

A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image

https://github.com/bogedy/intro_dfc

Deep Feature Consistent Variational Autoencoder

https://github.com/boom85423/Cartoon-style-Stickers-Generator

Mask R-CNN

https://github.com/boomb0om/pytorch-optimalstyletransfer

A Closed-form Solution to Universal Style Transfer

https://github.com/bordac6/PNNPPV_project

Stacked Hourglass Networks for Human Pose Estimation

https://github.com/boreshkinai/smpl-ik

SMPL-IK: Learned Morphology-Aware Inverse Kinematics for AI Driven Artistic Workflows

https://github.com/borglab/gtsfm

SuperGlue: Learning Feature Matching with Graph Neural Networks

https://github.com/borisdayma/dalle-mini

Zero-Shot Text-to-Image Generation

https://github.com/boschresearch/numerics_independent_neural_odes

Neural Ordinary Differential Equations

https://github.com/boukhayma/3dhand

3D Hand Shape and Pose from Images in the Wild

https://github.com/bouracha/Gen_Motion

Learning Trajectory Dependencies for Human Motion Prediction

https://github.com/bouracha/OoDMotion

Learning Trajectory Dependencies for Human Motion Prediction

https://github.com/bowu1004/instance_segmentation_RealSense

Mask R-CNN

https://github.com/bprabhakar/text-to-image

AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

https://github.com/brandontrabucco/da-fusion

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

https://github.com/brightyoun/Video-Style-Transfer

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/brijmohan/adaptive_voice_conversion

One-shot Voice Conversion by Separating Speaker and Content Representations with Instance Normalization

https://github.com/brucechou1983/CheXNet-Keras

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

https://github.com/bruceyanwee/fast_style_transfer_v2.0

Arbitrary Style Transfer via Multi-Adaptation Network

https://github.com/bshall/VectorQuantizedCPC

Vector-quantized neural networks for acoustic unit discovery in the ZeroSpeech 2020 challenge

https://github.com/bshall/ZeroSpeech

Vector-quantized neural networks for acoustic unit discovery in the ZeroSpeech 2020 challenge

https://github.com/bshall/hubert

A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion

https://github.com/buddly27/stylish

A Neural Algorithm of Artistic Style

https://github.com/busyboxs/What-I-have-star

Mask R-CNN

https://github.com/busyboxs/faster_rcnn_voc

Mask R-CNN

https://github.com/bw2color/bw2color

XGBoost: A Scalable Tree Boosting System

https://github.com/bywords/lang-style-transfer-legacy

Style Transfer from Non-Parallel Text by Cross-Alignment

https://github.com/c-yn/ChaIR

https://github.com/c-yn/ConvIR

https://github.com/c-yn/FSNet

https://github.com/c-yn/IRNeXt

https://github.com/caffe2/aicamera-style-transfer

A Neural Algorithm of Artistic Style

https://github.com/cai-jianfeng/ROMP_mindspore

Monocular, One-stage, Regression of Multiple 3D People

https://github.com/caidao22/pkg-cams

Neural Ordinary Differential Equations

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