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deffand's Projects

2020codecraft icon 2020codecraft

2020华为软挑初赛粤港澳赛区第一,复赛粤港澳赛区A榜第一解决方案

adareg-monodispnet icon adareg-monodispnet

Repository for Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction (CVPR2019)

anvil icon anvil

Anvil is a cross-platform framework for Vulkan

awesome-python-login-model icon awesome-python-login-model

😮python模拟登陆一些大型网站,还有一些简单的爬虫,希望对你们有所帮助❤️,如果喜欢记得给个star哦🌟

caffe icon caffe

Caffe: a fast open framework for deep learning.

centernet icon centernet

Codes for our paper "CenterNet: Keypoint Triplets for Object Detection" .

cs-books icon cs-books

📚 Computer Science Books 计算机技术类书籍 PDF

cs-notes icon cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

d2l-zh icon d2l-zh

《动手学深度学习》,英文版即伯克利深度学习(STAT 157,2019春)教材。面向中文读者、能运行、可讨论。

dcgan-tensorflow icon dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

dcgan.torch icon dcgan.torch

A torch implementation of http://arxiv.org/abs/1511.06434

deep3d icon deep3d

Automatic 2D-to-3D Video Conversion with CNNs

deepfashion2 icon deepfashion2

DeepFashion2 Dataset https://arxiv.org/pdf/1901.07973.pdf

deeplearning-500-questions icon 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,近30万字。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

deepmatchvo icon deepmatchvo

Implementation of ICRA 2019 paper: Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation

densefusion icon densefusion

"DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion" code repository

depth-vo-feat icon depth-vo-feat

Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction

detectron icon detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

detectron.pytorch icon detectron.pytorch

A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available. Supports PyTorch 1.0

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