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LucasLee-ff's starred repositories

QA-Survey-CN

北京航空航天大学大数据高精尖中心自然语言处理研究团队开展了智能问答的研究与应用总结。包括基于知识图谱的问答（KBQA），基于文本的问答系统（TextQA），基于表格的问答系统（TableQA）、基于视觉的问答系统（VisualQA）和机器阅读理解（MRC）等，每类任务分别对学术界和工业界进行了相关总结。

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Chinese-LLaMA-Alpaca-2

中文LLaMA-2 & Alpaca-2大模型二期项目 + 64K超长上下文模型 (Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models)

Language:PythonApache-2.0694700

baby-llama2-chinese

用于从头预训练+SFT一个小参数量的中文LLaMa2的仓库；24G单卡即可运行得到一个具备简单中文问答能力的chat-llama2.

Language:PythonMIT224000

Chinese-LLaMA-Alpaca

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

Language:PythonApache-2.01769100

PicQuery

🔍 Search local images with natural language on Android, powered by OpenAI's CLIP model. / 在 Android 上用自然语言搜索本地图片 (基于 OpenAI 的 CLIP 模型)

Language:KotlinMIT19300

Confident_Learning_for_Object_Detection

Use Confident Learning to clean out noise labels in object detection dataset, based on mmdetection

Language:Python600

Unsupervised_Anomaly_Detection

UAD algorithms, include padim, stfpm, patchcore and ours local coreset

Language:Python700

Summary-of-RGB-T-Salient-Object-Detection-and-Semantic-segmentation

Summary of RGB-T Salient Object Detection, Semantic segmentation and Crowd Counting.

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pytorch-OpCounter

Count the MACs / FLOPs of your PyTorch model.

Language:PythonMIT473100

A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Crowd Counting, RGB-T Fusion Tracking.

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RGB-T-fusion-tracking-papers-and-results

The papers and results about RGB-T fusion tracking

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mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

Language:PythonApache-2.0757000

SOD100K

The official repo of the TPAMI 2021/ECCV 2020 work CSNet: A Highly Efficient Model with 100K Parameters to Study the Semantics of Salient Object Detection

Language:Python24100