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100-nlp-papers

NLP必读经典文献100篇 100 Must-Read NLProc Papers

2-entity-ransac

2-Entity RANSAC：在变化的环境中进行稳健的视觉定位 2-Entity-RANSAC for monocular and multiple camera system

2d_detection

TensorFlow实现的SqueezeDet自驾目标检测 TensorFlow implementation of SqueezeDet, trained on the KITTI dataset.

3d-bonet

3D-BoNet：比3D点云实例分割算法快10倍 3D-BoNet in Tensorflow (NeurIPS 2019, Spotlight)

3d-convolutional-speaker-recognition

TensorFlow的3D卷积神经网络做说话人识别

3d-pose-baseline

TensorFlow实现的3D人体姿态估计Baseline A simple baseline for 3d human pose estimation in tensorflow.

3dcnn.torch

Volumetric CNN for feature extraction and object classification on 3D data.

3dmatch-toolbox

3DMatch基于卷积网络的三维点云配准 3DMatch - a 3D ConvNet-based local geometric descriptor for aligning 3D meshes and point clouds.

3dmm_cnn

2D人脸转3D：(基于超深网络)由非限定2D人脸端到端生成3D人脸模型 Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network

a-loam

Advanced implementation of LOAM

acapellabot

基于卷积神经网络的歌曲人声分离 Acapella Extraction with a ConvNet

acsc

非重复雷达与相机自动标定Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems

act

Real-time 'Actor-Critic' tracking

action-recognition-visual-attention

Action recognition using soft attention based deep recurrent neural networks

active-slam-with-cartographer

This work contains a modified version of cartographer_frontier_detection and rrt_exploration. We implement an active exploration process and improve its robustness and performance. More details are described in the paper "Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration" (IROS2020).

active-speakers-context

从视频识别出谁在说话 Code for the Active Speakers in Context Paper (CVPR2020)

ad_examples

异常检测方法示例集锦 A collection of popular anomaly detection methods (iid/point-based and time series) including active learning for anomaly detection/discovery, description for diversity/explanation/interpretability. With a deeper analysis of incorporating label feedback with ensemble and tree-based detectors. Includes results-plots and illustrations for most approaches covered.

adversarial-frcnn

Caffe实现的A-Fast-RCNN A-Fast-RCNN (CVPR 2017)

adversarialnetspapers

对抗网络经典论文/代码/案例汇总 The classical Papers about adversial nets

age-and-gender-classification

(Caffe/OpenCV)CNN年龄/性别分类 Age and Gender Classification using Convolutional Neural Network

age-gender-estimate-tf

TensorFlow实现的人脸性别/年龄识别 Face age and gender estimate using TensorFlow

ai-notebooks

algorithmvisualizer

算法图形可视化Algorithm Visualizer

alicemind

读图会意 看图说话 超过人类

all-conv-keras

从基本概念到实现，全卷积网络实现更简洁的图像识别 全卷积网络：更简单 更小 更好 All Convolutional Network: (https://arxiv.org/abs/1412.6806#) implementation in Keras

amazon_forest_computer_vision

Kaggle亚马逊丛林卫星图像标记竞赛方案 Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks

amc-compressed-models

[ECCV 2018] Compressed models from AMC: AutoML for Model Compression and Acceleration on Mobile Devices.

android-yolo

在安卓设备上使用YOLO实行实时物体检测 Real-time object detection on Android using the YOLO network with TensorFlow

android_apps

ROS android Applications built on top of the rosjava android libraries.

androidtensorflowmachinelearningexample

Android平台TensorFlow机器学习实例 Android TensorFlow MachineLearning Example (Building TensorFlow for Android)