A team of researchers from the Chinese Academy of Sciences and the City University of Hong Kong has introduced a local-to-global approach that can generate lifelike human portraits from relatively rudimentary sketches.
Facebook this week released Detection Transformers (DETR), a new approach for object detection and panoptic segmentation tasks that uses a completely different architecture than previous object detection systems.
Researchers from the University of Bristol, the University of Toronto and the University of Catania explain how they created Epic-Kitchens and introduce new baselines that emphasize the multimodal nature of the largest such egocentric video benchmark.
A team of researchers from Russian AI startup OSAI recently introduced the real-time neural network TTNet, designed for processing high-resolution table tennis videos with both temporal and spatial data.
Just as biologists gain insights into organisms by putting model specimens under their microscopes, AI Microscope was designed to help researchers analyze the features that form inside leading CV models.
In a bid to generate high-resolution images showing realistic daytime changes while keeping accurate scene semantics, researchers have proposed a novel image-to-image translation model, HiDT (High Resolution Daytime Translation).
A team of researchers from NVIDIA and Heidelberg University recently introduced an open-source self-supervised learning technique for viewpoint estimation of general objects that draws on such freely available Internet images.
Their proposed framework outperforms state-of-the-art approaches for 3D reconstructions from 2D and 2.5D data, achieving 12 percent better performance on average in the ShapeNet benchmark dataset and up to 19 percent for certain classes of objects.
Researchers from the University of Chicago Oriental Institute (OI) and the Department of Computer Science have introduced an artificial intelligence tool called DeepScribe designed to read cuneiform tablets from 25 centuries ago.