Our model is based on a conditional generative adversarial network, generating images considering the original pose and image background.
SOTA for Face Anonymization on 2019_test set (using extra training data)
Large-scale language models show promising text generation capabilities, but users cannot easily control particular aspects of the generated text.
In this paper, we introduce Neural Oblivious Decision Ensembles (NODE), a new deep learning architecture, designed to work with any tabular data.
👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)
This paper shows how Long Short-term Memory recurrent neural networks can be used to generate complex sequences with long-range structure, simply by predicting one data point at a time.
In existing CNN based detectors, the backbone network is a very important component for basic feature extraction, and the performance of the detectors highly depends on it.
SOTA for Object Detection on COCO test-dev
In this paper we show that the likelihood objective itself is at fault, resulting in a model that assigns too much probability to sequences that contain repeats and frequent words unlike the human training distribution.