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Found 7 papers, 1 papers with code
Neural Routing by Memory
However, they use the same procedure sequence for all inputs, regardless of the intermediate features. This paper proffers a simple yet effective idea of constructing parallel procedures and assigning similar intermediate features to the same specialized procedures in a divide-and-conquer fashion.
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution
One challenge of semantic segmentation is to deal with the object scale variations and leverage the context.
Bootstrap Model Ensemble and Rank Loss for Engagement Intensity Regression
Based on our winner solution last year, we mainly explore head features and body features with a bootstrap strategy and two novel loss functions in this paper.
Super-Identity Convolutional Neural Network for Face Hallucination
Face hallucination is a generative task to super-resolve the facial image with low resolution while human perception of face heavily relies on identity information.
Detecting Faces Using Inside Cascaded Contextual CNN
Deep Convolutional Neural Networks (CNNs) achieve substantial improvements in face detection in the wild.
A Discriminative Feature Learning Approach for Deep Face Recognition
In most of the available CNNs, the softmax loss function is used as the supervision signal to train the deep model.
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
Face detection and alignment in unconstrained environment are challenging due to various poses, illuminations and occlusions.
Ranked #9 on
Face Detection
on WIDER Face (Easy)
