The National Science Foundation awarded a $281,367 Project Grant to the Rochester Institute of Technology under the Social, Behavioral, and Economic Sciences program (CFDA 47.075). The three-year award will fund research into visual perception of three-dimensional object shape from patterns of image shading and contours. The researchers will study how the human visual system processes and interprets information about an object's 3D properties. They will incorporate optical effects typically...
The National Science Foundation Office of Integrative Activities awarded North Carolina Agricultural and Technical State University a $373,588 Project Grant under the Social, Behavioral, and Economic Sciences federal grant program (CFDA 47.075) to support research titled "Excellence in Research: Predicting Computations that Lead to a Stable Perception of Object Lightness under Spectral Variabilities of the Visual Scene." The three-year award beginning August 1, 2021 will fund...
The National Science Foundation (NSF) awarded a Project Grant of $599,649 to Carnegie Mellon University (CMU) under the Computer and Information Science and Engineering (CFDA 47.070) program. The goal of this 3-year project, which commenced on April 15, 2024, is to develop perception systems that can infer the 3D structure of generic objects or scenes from 2D images, even with partial observations. Key technical efforts will include formulating mechanisms for learning novel 3D generative...
This three-year $476,113 project grant from the National Science Foundation's Social, Behavioral, and Economic Sciences program (CFDA 47.075) supports research at Northeastern University to advance understanding of human color vision processes. The grantee will employ novel psychophysical methods to measure behavioral responses triggered by color within the first fraction of a second of visual stimulus, and explore how those responses change over time across a range of colors, contrasts and...
This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) aims to enhance computer vision capabilities for understanding and recognizing shapes in images and 3D data. The $299,964 award to The Research Foundation for the State University of New York, doing business as Stony Brook University, will develop new deep learning frameworks and graph-transformer-based approaches to enable computers to focus on the critical parts of...
The Ohio State University will provide collaborative research on robust perception through end-user adaptation under a $310,000 National Science Foundation Project Grant for the Computer and Information Science and Engineering program. The four-year award runs from October 2021 through September 2025. As part of the NSF's CSE program to support investigator-initiated research and education in computing, communications, and information science and engineering, the University will advance...
This federal Project Grant award of $283,832, made by the National Science Foundation's (NSF) Division of Behavioral and Cognitive Sciences under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program, supports research to investigate how the human brain creates the perception of visual stability during naturalistic attention tasks. The project aims to test whether the latest AI-powered vision-language models can generate plausible visual scenes in real-time using limited input...
This NSF-BSF project grant award of $233,958 to Brown University will support research to investigate the interdependence between perception, cognition, and action. The project aims to understand how specific actions can influence visual perception, and which aspects of visual processing are improved when preparing to act. It will use a combination of behavioral, psychophysical, physiological, and computational approaches. The research team will also engage in outreach activities to promote...
This National Science Foundation (NSF) Division of Information and Intelligent Systems (CFDA #47.070) $1,034,326 Project Grant awarded to Brown University supports collaborative research to bridge the semantic-metric gap in multinocular 3D vision systems. The project aims to address key technical challenges in 3D computer vision, such as handling blurry/textureless images, leveraging redundant image data, and connecting geometric point clouds to semantic scene representations. The research...
This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research at the University of California, San Diego (UCSD) to develop theoretical frameworks and computational methods for reconstructing complex 3D shapes using neural implicit representations. The key objectives are to enable the reconstruction of 3D shapes with intricate topologies, such as objects with holes, and to allow...