jeong-tae's starred repositories
InternLM-XComposer
InternLM-XComposer2 is a groundbreaking vision-language large model (VLLM) excelling in free-form text-image composition and comprehension.
pdfminer.six
Community maintained fork of pdfminer - we fathom PDF
DPText-DETR
[AAAI'23 Oral] DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer
Deformable-DETR
Deformable DETR: Deformable Transformers for End-to-End Object Detection.
SynthText_CH
[SynthText Chinese] Improved code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Vedaldi, Andrew Zisserman, CVPR 2016.
SynthText_kr
[KOREAN] Code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Vedaldi, Andrew Zisserman, CVPR 2016.
image-text-localization-recognition
A general list of resources to image text localization and recognition 场景文本位置感知与识别的论文资源与实现合集 シーンテキストの位置認識と識別のための論文リソースの要約
glass-text-spotting
Official implementation for "GLASS: Global to Local Attention for Scene-Text Spotting" (ECCV'22)
GenerativeImage2Text
GIT: A Generative Image-to-text Transformer for Vision and Language
SNIP-filter-level-pytorch
Evaluate sensitivity of channel/vector connection to decrease width/depth of network. Which will accelerate inference speed and reduce storage usage without any other module or support
SwinTextSpotter
Pytorch re-implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition (CVPR 2022)
RSA-CVPR19-release
code for CVPR paper "Representation Similarity Analysis for Efficient Task Taxonomy and Transfer Learning"
DAVAR-Lab-OCR
OCR toolbox from Davar-Lab
hello_tf_c_api
Neural Network TensorFlow C API
SuperPoint
Efficient neural feature detector and descriptor
locating-objects-without-bboxes
PyTorch code for "Locating objects without bounding boxes" - Loss function and trained models
pixel-level-contrastive-learning
Implementation of Pixel-level Contrastive Learning, proposed in the paper "Propagate Yourself", in Pytorch
deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications