Moire patterns, appearing as color distortions, severely degrade image and video qualities when filming a screen with digital cameras.
Next, a fully convolutional network is proposed to achieve the low-light image enhancement by fusing colored raw data with synthesized monochrome raw data.
We further integrate HRec with RMS and derive our recommendation solution, RMS-HRec, that automatically utilizes the effective meta-paths.
We make it open-source for fair and comprehensive competitions between offline RL algorithms with complete datasets and checkpoints being provided.
WOO takes a unified video backbone to simultaneously extract features for actor location and action classification.
Graph neural networks (GNNs) are a popular class of parametric model for learning over graph-structured data.
Ranked #4 on Node Property Prediction on ogbn-mag
This paper describes Facebook AI's submission to the WAT 2019 Myanmar-English translation task.
In this work, we first empirically show that self-training is able to decently improve the supervised baseline on neural sequence generation tasks.
While we live in an increasingly interconnected world, different places still exhibit strikingly different cultures and many events we experience in our every day life pertain only to the specific place we live in.
Graph embedding methods produce unsupervised node features from graphs that can then be used for a variety of machine learning tasks.
Ranked #1 on Link Prediction on YouTube (Macro F1 metric)
In this paper, we design a framework for training deformable classifiers, where latent transformation variables are introduced, and a transformation of the object image to a reference instantiation is computed in terms of the classifier output, separately for each class.