HyeonwooNoh

OpenAI

Pinned Repositories

caffe
modified version of caffe which support DeconvNet and DecoupledNet
Language:C++102 15 1769
DeconvNet
DeconvNet : Learning Deconvolution Network for Semantic Segmentation
Language:Matlab325 22 14151
DecoupledNet
DecoupledNet: Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
Language:Python74 12 441
DPPnet
DPPnet: Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction
Language:Lua95 14 1345
my_ubuntu_settings
Language:Vim script10 2 02
RAU_VQA
Training Recurrent Answering Units with Joint Loss Minimization for VQA
Language:Lua6 2 15
voc_classification
Language:Python29 2 08
VQA-Transfer-ExternalData
Transfer Learning via Unsupervised Task Discovery for Visual Question Answering
Language:Python20 3 02
vqa_task_discovery
Transfer Learning via Unsupervised Task Discovery for Visual Question Answering
Language:Python32 4 04
VQABrowser
Qualitative / quantitative evaluation tool for Visual Question Answering dataset.
Language:Python6 3 01

HyeonwooNoh's Repositories

HyeonwooNoh/vqa_task_discovery
Transfer Learning via Unsupervised Task Discovery for Visual Question Answering
Language:Python32 4 04
HyeonwooNoh/voc_classification
Language:Python29 2 08
HyeonwooNoh/VQA-Transfer-ExternalData
Transfer Learning via Unsupervised Task Discovery for Visual Question Answering
Language:Python20 3 02
HyeonwooNoh/my_ubuntu_settings
Language:Vim script10 2 02
HyeonwooNoh/RAU_VQA
Training Recurrent Answering Units with Joint Loss Minimization for VQA
Language:Lua6 2 15
HyeonwooNoh/HyeonwooNoh.github.io
Language:HTML2 2 0
HyeonwooNoh/Gumbel-Softmax-VAE-in-tensorflow
Semi-Supervised Learning with Categorical VAE (experimented on MNIST)
Language:Python1 4 0
HyeonwooNoh/ViZDoomDeterministic
Language:C++1 4 0
HyeonwooNoh/bi-att-flow
Bidirectional Attention Flow
Language:Python
HyeonwooNoh/bottom-up-attention
Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
Language:Jupyter Notebook
HyeonwooNoh/bottom-up-attention-vqa
An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.
Language:Python3 0
HyeonwooNoh/clevr-dataset-gen
A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
Language:Python
HyeonwooNoh/densecap
Dense image captioning in Torch
Language:Jupyter Notebook2 0
HyeonwooNoh/ffjpeg
a simple jpeg codec.
Language:C2 0
HyeonwooNoh/gym-minigrid
Minimalistic gridworld package for OpenAI Gym
Language:Python
HyeonwooNoh/maml
Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
Language:Python
HyeonwooNoh/MulLowBiVQA
Hadamard Product for Low-rank Bilinear Pooling
Language:Lua
HyeonwooNoh/NerveNet
Language:Python
HyeonwooNoh/nmt
TensorFlow Neural Machine Translation Tutorial
Language:Python
HyeonwooNoh/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Language:Python3 0
HyeonwooNoh/pytorch-vqa
Strong baseline for visual question answering
Language:Jupyter Notebook1
HyeonwooNoh/Relation-Network-Tensorflow
Tensorflow implementations of Relational Networks and a VQA dataset named Sort-of-CLEVR proposed by DeepMind.
Language:Python3 0
HyeonwooNoh/rl-starter-files
RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code
Language:Python
HyeonwooNoh/sac
Soft Actor-Critic
Language:Python
HyeonwooNoh/Settings
2 01
HyeonwooNoh/Temporary
2 0
HyeonwooNoh/tensorflow_hw
Computation using data flow graphs for scalable machine learning
Language:C++
HyeonwooNoh/torch-ac
Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms: A2C and PPO
Language:Python3 0
HyeonwooNoh/Visual-Question-Answering
CNN+LSTM, Attention based, and MUTAN-based models for Visual Question Answering
Language:Python3 0
HyeonwooNoh/wide-residual-networks-iwdrop
3.8% and 18.3% on CIFAR-10 and CIFAR-100
Language:Lua2 0