Pinned Repositories
Algorithm_Interview_Notes-Chinese
2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记
faiss-web-service
A web service build on top of Facebook's Faiss
100-Days-Of-ML-Code
100 Days of ML Coding
100-Days-Of-ML-Code-1
100-Days-Of-ML-Code中文版
3D-Vision-and-Touch
When told to understand the shape of a new object, the most instinctual approach is to pick it up and inspect it with your hand and eyes in tandem. Here, touch provides high fidelity localized information while vision provides complementary global context. However, in 3D shape reconstruction, the complementary fusion of visual and haptic modalities remains largely unexplored. In this paper, we study this problem and present an effective chart-based approach to fusing vision and touch, which leverages advances in graph convolutional networks. To do so, we introduce a dataset of simulated touch and vision signals from the interaction between a robotic hand and a large array of 3D objects. Our results show that (1) leveraging both vision and touch signals consistently improves single-modality baselines, especially when the object is occluded by the hand touching it; (2) our approach outperforms alternative modality fusion methods and strongly benefits from the proposed chart-based structure; (3) reconstruction quality boosts with the number of grasps provided; and (4) the touch information not only enhances the reconstruction at the touch site but also extrapolates to its local neighborhood.
AlphaTree-graphic-deep-neural-network
将深度神经网络中的一些模型 进行统一的图示，便于大家对模型的理解
awesome-image-classification
A curated list of deep learning image classification papers and codes
awesome-lane-detection
lane detection
awesome-object-detection
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
bestofml
The best resources around Machine Learning
ahappycutedog's Repositories
ahappycutedog/Grasping-state-assessment
ahappycutedog/touchsim
A Python implementation of the TouchSim model to simulate peripheral tactile responses.
ahappycutedog/3D-Vision-and-Touch
When told to understand the shape of a new object, the most instinctual approach is to pick it up and inspect it with your hand and eyes in tandem. Here, touch provides high fidelity localized information while vision provides complementary global context. However, in 3D shape reconstruction, the complementary fusion of visual and haptic modalities remains largely unexplored. In this paper, we study this problem and present an effective chart-based approach to fusing vision and touch, which leverages advances in graph convolutional networks. To do so, we introduce a dataset of simulated touch and vision signals from the interaction between a robotic hand and a large array of 3D objects. Our results show that (1) leveraging both vision and touch signals consistently improves single-modality baselines, especially when the object is occluded by the hand touching it; (2) our approach outperforms alternative modality fusion methods and strongly benefits from the proposed chart-based structure; (3) reconstruction quality boosts with the number of grasps provided; and (4) the touch information not only enhances the reconstruction at the touch site but also extrapolates to its local neighborhood.
ahappycutedog/LSTM-Haptic-Fusion
ahappycutedog/PyRetri
Open source deep learning based unsupervised image retrieval toolbox built on PyTorch🔥
ahappycutedog/chineseocr_lite
超轻量级中文ocr，支持竖排文字识别, 支持ncnn推理 , psenet(8.5M) + crnn(6.3M) + anglenet(1.5M) 总模型仅17M
ahappycutedog/Visual-Tactile_Dataset
A novel visual-tactile dataset for robotic manipulation
ahappycutedog/senet.pytorch
PyTorch implementation of SENet
ahappycutedog/Python
All Algorithms implemented in Python
ahappycutedog/faiss-web-service
A web service build on top of Facebook's Faiss
ahappycutedog/CDCS
Chinese Data Competitions' Solutions
ahappycutedog/bestofml
The best resources around Machine Learning
ahappycutedog/keras-squeeze-excite-network
Implementation of Squeeze and Excitation Networks in Keras
ahappycutedog/AlphaTree-graphic-deep-neural-network
将深度神经网络中的一些模型 进行统一的图示，便于大家对模型的理解
ahappycutedog/awesome-image-classification
A curated list of deep learning image classification papers and codes
ahappycutedog/awesome-object-detection
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
ahappycutedog/pwc
Papers with code. Sorted by stars. Updated weekly.
ahappycutedog/machinelearning
My blogs and code for machine learning. http://cnblogs.com/pinard
ahappycutedog/OCR_TF_CRNN_CTC
Extremely simple implement for CRNN by Tensorflow
ahappycutedog/SCDA_keras
A keras and tensorflow implementation of the "Selective Convolutional Descriptor Aggregation" algorithm
ahappycutedog/YOLOv3_TensorFlow
Complete YOLO v3 TensorFlow implementation. Support training on your own dataset.
ahappycutedog/awesome-lane-detection
lane detection
ahappycutedog/ChineseNlpCorpus
搜集、整理、发布 中文 自然语言处理 语料/数据集，与 有志之士 共同 促进 中文 自然语言处理 的 发展。
ahappycutedog/keras-retinanet
Keras implementation of RetinaNet object detection.
ahappycutedog/100-Days-Of-ML-Code-1
100-Days-Of-ML-Code中文版
ahappycutedog/100-Days-Of-ML-Code
100 Days of ML Coding
ahappycutedog/Hands-on-Machine-Learning
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
ahappycutedog/Machine-Learning
:zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
ahappycutedog/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15个章节，近20万字。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scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
ahappycutedog/chinese_ocr
CTPN + DenseNet + CTC based end-to-end Chinese OCR implemented using tensorflow and keras