MinglangQiao

MinglangQiao's Stars

• fengdu78/lihang-code

  《统计学习方法》的代码实现

  Language:Jupyter Notebook18.9k537496.3k

• ShiqiYu/libfacedetection

  An open source library for face detection in images. The face detection speed can reach 1000FPS.

  Language:C++12.3k5313183k

• karpathy/neuraltalk

  NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.

  Language:Python5.4k439381.3k

• sgrvinod/a-PyTorch-Tutorial-to-Image-Captioning

  Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

  Language:Python2.8k24187711

• jcjohnson/densecap

  Dense image captioning in Torch

  Language:Jupyter Notebook1.6k6889430

• peteanderson80/bottom-up-attention

  Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

  Language:Jupyter Notebook1.4k26117379

• BangguWu/ECANet

  Code for ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

  Language:Python1.2k1568198

• DeepRNN/image_captioning

  Tensorflow implementation of "Show, Attend and Tell: Neural Image Caption Generation with Visual Attention"

  Language:Python7852676354

• hengyuan-hu/bottom-up-attention-vqa

  An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.

  Language:Python7503448182

• xiahouzuoxin/notes

  研究生阶段的一些文章（技术、思考、读书笔记、日常琐事等）

  Language:HTML518424243

• wenguanwang/SODsurvey

  Salient Object Detection in the Deep Learning Era: An In-Depth Survey

  382101169

• jiasenlu/AdaptiveAttention

  Implementation of "Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning"

  Language:Jupyter Notebook334132574

• peteanderson80/Up-Down-Captioner

  Automatic image captioning model based on Caffe, using features from bottom-up attention.

  Language:Jupyter Notebook24382869

• cesc-park/attend2u

  🖼️ Attend to You: Personalized Image Captioning with Context Sequence Memory Networks. In CVPR, 2017. Expanded : Towards Personalized Image Captioning via Multimodal Memory Networks. In IEEE TPAMI, 2018.

  Language:Python209131857

• zjuchenlong/sca-cnn.cvpr17

  Image Captions Generation with Spatial and Channel-wise Attention

  Language:Python20812073

• poojahira/image-captioning-bottom-up-top-down

  PyTorch implementation of Image captioning with Bottom-up, Top-down Attention

  Language:Python16233338

• Theigrams/Mathematical-optimization

  数学系本科三年级《最优化理论与方法》

  Language:Mathematica1554148

• yxlijun/Pyramidbox.pytorch

  Pyramidbox implement with pytorch

  Language:Python15572147

• yuantailing/tunet-python

  TUNet 2018 认证协议的纯 python 实现，含 auth4 / auth6 / net 认证。适用于服务器在无人交互时自动认证

  Language:Python1527032

• deepsemantic/image_captioning

  Image Captioning with Deep Bidirectional LSTMs

  Language:C++8561036

• rohitrango/objects-that-sound

  Unofficial Implementation of Google Deepmind's paper `Objects that Sound`

  Language:Python835816

• Dong-JinKim/DenseRelationalCaptioning

  Code of Dense Relational Captioning

  Language:Lua6731713

• linjieyangsc/densecap

  Dense captioning with joint inference and visual context

  Language:C++5331024

• zhangludl/code-and-dataset-for-CapSal

  This project provides the code and datasets for 'CapSal: Leveraging Captioning to Boost Semantics for Salient Object Detection', CVPR 2019.

  Language:Python501816

• cindydeng1991/Wavelet-Domain-Style-Transfer-for-an-Effective-Perception-distortion-Tradeoff-in-Single-Image-Super-

  ICCV 2019 oral presentation

  Language:Jupyter Notebook43334

• hsientzucheng/CP-360-Weakly-Supervised-Saliency

  CP-360-Weakly-Supervised-Saliency

  Language:Python28425

• SenHe/Human-Attention-in-Image-Captioning

  22201

• blankblankblank123/MCANet

  Implement of Multi Co-Attention Network(MCANet)

  Language:Python151

• boschresearch/GridSaliency-ToyDatasetGen

  Code for toy dataset generation of "Grid Saliency for Context Explanations of Semantic Segmentation" (https://arxiv.org/abs/1907.13054)

  Language:Python11531

• MC-2-Lab/MC-2

  www.buaamc2.net

  Language:JavaScript100010