nothingeasy's repositories
AWESOME-FER
A reading list of top Conferences & Journals, focused on facial expression recognition (FER), facial action unit (FAU) recognition and other emotion-related papers.
awesome-python3-webapp
小白的Python入门教程实战篇：网站+iOS App源码→ http://t.cn/R2PDyWN 赞助→ http://t.cn/R5bhVpf
CovPoolFER
Covariance Pooling for Facial Expression Recognition
curriculum_learning
Code implementing the experiments described in the paper "On The Power of Curriculum Learning in Training Deep Networks" by Hacohen & Weinshall (ICML 2019)
deep-learning-coursera
Deep Learning Specialization by Andrew Ng on Coursera.
Deformable-ConvNets
Deformable Convolutional Networks
ExprGAN
Facial Expression Editing with Controllable Expression Intensity
fast-MPN-COV
@CVPR2018: Efficient unrolling iterative matrix square-root normalized ConvNets, implemented by PyTorch (and code of B-CNN,Compact bilinear pooling etc.) for training from scratch & finetuning.
FECNet
A Keras implementation of FECNet, which proposed in "A Compact Embedding for Facial Expression Similarity"
ISDA-for-Deep-Networks
An efficient implicit semantic augmentation method, complementary to existing non-semantic techniques.
learn-to-cluster
Learning to Cluster Faces on an Affinity Graph (CVPR 2019)
ML_GCN
PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.
Non-local_pytorch
Implementation of Non-local Block.
NumpyWDL
Implement Wide & Deep algorithm by using NumPy
person_search_gcn
This repository hosts the code for our paper “Learning Context Graph for Person Search”, CVPR2019 Oral
pygcn
Graph Convolutional Networks in PyTorch
pytorch-pruning
PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
ran_replicate
A PyTorch re-implementation of Weakly Supervised Facial Action Unit Recognition through Adversarial Training
RandWireNN
Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"
research-curriculumnet
CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images
SAN
Second-order Attention Network for Single Image Super-resolution (CVPR-2019)
vision
Datasets, Transforms and Models specific to Computer Vision
WS-DAN.PyTorch
A PyTorch implementation of WS-DAN (Weakly Supervised Data Augmentation Network) for FGVC (Fine-Grained Visual Classification)