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Researchers from Google AI have presented an interesting novel method for object detection that takes into account the image context for improving detection performance. As part of a large project…

NVIDIA researchers have presented their new project StyleGAN2 at this year’s CVPR 2020. The novel method behind StyleGAN2 is based on previous advancements in generative modeling and the wide known…

Researchers from Facebook AI have presented a novel image segmentation method that can produce high-quality, precise segmentation masks. The method is based on a new neural network module called PointRend,…

A group of researchers from Duke University has proposed a novel state-of-the-art method for image super-resolution that is able to generate realistic very high-resolution images from a low-resolution input image.…

Researchers from Facebook AI have developed a neural network model that can translate code from one programming language to another. Their proposed model, called TransCoder is able to translate between…

A group of researchers from the Shangai Tech University, University of Leeds, and Zhegjiang University have developed a deep neural network for recovering 3D editable objects from a single image.…

In a novel paper published on this year’s CVPR2020, researchers from the Samsung AI Center in Moscow led by Konstantin Sofiiuk, describe their new method for interactive segmentation named f-BRS.…

A group of researchers from Tel Aviv University has developed a deep neural network model that reconstructs surface meshes directly from a given input point cloud. In their recent paper,…

Facebook AI has announced that they have developed a new approach to object detection called DETR which relies on Transformers to provide end-to-end object detection which matches the performance of…

NVIDIA has created a fully functional version of the popular PAC-MAN game using deep neural networks without using a game engine. Researchers from NVIDIA have presented the new and powerful…

A group of researchers from the University of Alberta has proposed new neural network architecture for salient object detection called U² Net. In their recent paper, researchers argue that most…

In a recent paper, researchers from the University of Freiburg, Germany, have proposed a new state-of-the-art CNN model for panoptic segmentation which also outperforms all existing models in terms of…

Researchers from Google AI have developed and released a new dataset for few-shot learning called Meta Dataset. The novel dataset is in fact attributed as a “dataset of datasets” and…

A group of researchers from the RWTH Aachen University has proposed a deep learning based method for transforming on-road images to semantically segmented bird-eye view (BEV) image. Semantic segmentation has…

Facebook AI has announced the release of a new challenge and dataset called “Hateful Memes”. In their blog post, researchers from Facebook describe the new challenge as another one in…

A group of researchers from the American Library of Congress has joined forces to create a large-scale dataset from newspaper content by analyzing over 16 million historic newspaper pages. As…

A group of researchers from the Hong Kong University of Science and Technology and Tencent have proposed a new segmentation model that provides high-resolution semantic segmentation without the need of…

A group of scientists from Amazon has published a new book on deep learning that is supposed to help students and developers learn about machine learning and deployment of machine…

Mapillary has released the world’s largest and most diverse open dataset for places recognition, that contains more than 1.6 million images. The new dataset, collected by researchers from Mapillary features…

OpenAI announced the release of Jukebox – a new neural network model that is able to generate realistic music of a wide variety of genres and styles. Automatic music generation…

A group of researchers from OSAI (Constanta) has designed a deep neural network for real-time analysis of table-tennis videos. Their model, named TTNet is able to extract temporal and spatial…