gagajian's starred repositories

PhotoMaker

PhotoMaker

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ArcNerf

Nerf and extensions in all

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GFPGAN

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

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iNAS

Open Source Neural Architecture Search Toolbox for Device-aware Image Dense Prediction & Official implementation of ICCV2021 "iNAS: Integral NAS for Device-Aware Salient Object Detection"

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HandyView

Handy image viewer based on PyQt5. Convenient for viewing and comparing :-)

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ESRGAN

ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.

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EDVR

Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. EDVR has been merged into BasicSR and this repo is a mirror of BasicSR.

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Real-ESRGAN

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

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BasicSR

Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.

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facexlib

FaceXlib aims at providing ready-to-use face-related functions based on current STOA open-source methods.

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crnn.pytorch

Convolutional recurrent network in pytorch

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DB

A PyTorch implementation of "Real-time Scene Text Detection with Differentiable Binarization".

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PaddleOCR

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

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text_renderer

Generate text images for training deep learning ocr model

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TextRecognitionDataGenerator

A synthetic data generator for text recognition

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awesome-deep-text-detection-recognition

A curated list of resources for text detection/recognition (optical character recognition ) with deep learning methods.

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DeepLearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06

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fucking-algorithm

刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.

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yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

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pytorch-YOLOv4

PyTorch ,ONNX and TensorRT implementation of YOLOv4

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yolov3

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

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Sequence-Level-Semantics-Aggregation

Sequence Level Semantics Aggregation for Video Object Detection

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STE-NVAN

Spatially and Temporally Efficient Non-local Attention Network for Video-based Person Re-Identification (BMVC 2019)

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awesome_video_person_reid

papers collection and understanding for video person re-identification

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SiamDW

[CVPR'19 Oral] Deeper and Wider Siamese Networks for Real-Time Visual Tracking

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MDENAS

Multinomial Distribution Learning for Effective Neural Architecture Search

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CBAM.PyTorch

Non-official implement of Paper:CBAM: Convolutional Block Attention Module

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CCNet

CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).

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