Popular GitHub Repositories for Weakly Supervised Segmentation

OpenMMLab Detection Toolbox and Benchmark

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

deep learning for image processing including classification and object-detection etc.

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

CVPR 2025 论文和开源项目合集

VIP cheatsheets for Stanford's CS 229 Machine Learning

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Image augmentation for machine learning experiments.

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

cvpr2024/cvpr2023/cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理

Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

100+ Chinese Word Vectors 上百种预训练中文词向量

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

Unsupervised text tokenizer for Neural Network-based text generation.

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

PyTorch implementation of the U-Net for image semantic segmentation with high quality images