Stars
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Photoshop CC v19 installer for Gnu/Linux
One-paper-one-short-contribution-summary of all latest image/burst/video Denoising papers with code & citation published in top conference and journal.
A lite C++ AI toolkit: 100+ models with MNN, ORT and TRT, including Det, Seg, Stable-Diffusion, Face-Fusion.
LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source …
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet
Crack LeetCode, not only how, but also why.
A Unified Toolkit for Deep Learning Based Document Image Analysis
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
This demo shows you how to build a single pose estimation algorithm in C++ using libtorch The model is trained using pytorch (Alphapose's SPPE model) , Check their github for training the model
Halpe: full body human pose estimation and human-object interaction detection dataset
人像matting数据集,包含34427张图像和对应的matting结果图。
ocr with yolo3 as feature extractor, implemented by keras, and accelerated by tensorrt
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
CTPN + DenseNet + CTC based end-to-end Chinese OCR implemented using tensorflow and keras
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
Document Rectification and Illumination Correction using a Patch-based CNN