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912-notes

清华大学计算机系考研专业课 (912) 笔记

aimet

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

aitools

tools for onnx check, compile profile & accuracy, and other functions

android-mobilefacenet-mtcnn-facedespoofing

Use tensorflow Lite on Android platform, integrated face detection (MTCNN), face anti spoofing (ECCV2018-FaceDeSpoofing) and face comparison (MobileFaceNet use InsightFace loss)

ann

Artificial-Neural-Network

apollo

An open autonomous driving platform

arcface

beverse

The official repository for BEVerse

bevformer

[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.

bevfusion

BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

binocular-positioning

单目标定+双目标定+深度图获取+三维坐标计算

books

books-and-note

:books: Book lists and Notes

caffe

Caffe: a fast open framework for deep learning.

caffe-int8-convert-tools

Generate a quantization parameter file for ncnn framework int8 inference

centerpoint-kitti

channel-pruning

Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)

chatglm-6b

ChatGLM-6B：开源双语对话语言模型 | An Open Bilingual Dialogue Language Model

chatglm-tuning

一种平价的chatgpt实现方案, 基于ChatGLM-6B + LoRA

chatgpt

🔮 ChatGPT Desktop Application (Mac, Windows and Linux)

chineseocr

yolo3+ocr

core_perception

cross_view_transformers

Cross-view Transformers for real-time Map-view Semantic Segmentation (CVPR 2022 Oral)

cryptoauth-openssl-engine

OpenSSL Engine implementation using ATECC508 for ECC key storage, ECDSA sign/verify, ECDH, and FIPS Random Number Generator (RNG).

cs231n.github.io

Public facing notes page

cvpr2019

cvpr2019／cvpr2018/cvpr2019 papers，极市团队整理

deblur

Deblur is a greedy deconvolution algorithm based on known read error profiles.

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

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[email protected] 版权所有，违权必究 Tan 2018.06

deeplearningsystem

Deep Learning System core principles introduction.