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yinxuping's Projects

paddleclas icon paddleclas

A treasure chest for visual recognition powered by PaddlePaddle

pix2depth icon pix2depth

DEPRECATED: Depth Map Estimation from Monocular Images

pwc icon pwc

Papers with code. Sorted by stars. Updated weekly.

pytorch-adain icon pytorch-adain

Unofficial pytorch implementation of 'Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization' [Huang+, ICCV2017]

pytorch-handbook icon pytorch-handbook

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

pytorch-image-models icon pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

pytorchdocs icon pytorchdocs

PyTorch 官方中文教程包含 60 分钟快速入门教程，强化教程，计算机视觉，自然语言处理，生成对抗网络，强化学习。欢迎 Star，Fork！

pytorchwct icon pytorchwct

This is the Pytorch implementation of Universal Style Transfer via Feature Transforms.

redegnet icon redegnet

From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution (ECCV 2022)

refinedet.pytorch icon refinedet.pytorch

A higher performance PyTorch implementation of Single-Shot Refinement Neural Network for Object Detection

robust-detection-benchmark icon robust-detection-benchmark

Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD)

roop icon roop

one-click deepfake (face swap)

scgan icon scgan

Semi-Cycled Generative Adversarial Networks for Real-World Face Super-Resolution

sms-bombing icon sms-bombing

短信轰炸，添加注册网站，实现更强劲的轰炸

sms_boomer icon sms_boomer

短信轰炸机，仅用于学习交流，请勿做违法行为

ssd.pytorch icon ssd.pytorch

A PyTorch Implementation of Single Shot MultiBox Detector

sspnet icon sspnet

SSPNet: Scale Selection Pyramid Network for Tiny Person Detection from UAV Images.

styletransfer icon styletransfer

Implementation of "Perceptual Losses for Real-Time Style Transfer and Super-Resolution" in PyTorch

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