This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) Project Grant award of $599,945 will fund the development of a 3D computer vision framework that integrates multiple sensing modalities, including RGB cameras, depth sensors, LiDAR, and event cameras. The research aims to enhance feature extraction, tracking, and large-scale scene reconstruction to improve perception accuracy and adaptability in unstructured environments. Key...
This $299,964 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to enhance computer vision and shape recognition capabilities. The primary institution, The Research Foundation for the State University of New York doing business as Stony Brook University, will develop novel deep learning and graph-based frameworks to teach computers to better perceive and understand the shape configuration and...
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 $1,090,678 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop computational algorithms that align deep neural networks (DNNs) with human visual processing. The project aims to rectify the growing "misalignment" between the behavior of large-scale DNNs and human cognition as AI systems become more capable. Researchers at Brown University will combine human...
This $348,956 federal Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program will fund research by Carnegie Mellon University (CMU) to develop advanced perception systems capable of understanding the 3D structure and actionable properties of the physical world. The project aims to bridge the gap between current computer vision techniques and human-level understanding of 3D environments and object...
This federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support the development of a hybrid, vision-centric framework that integrates intuitive and deliberate visual processing methods. The goal is to create more robust visual intelligence capabilities that can adapt to complex, real-world environments beyond static image datasets. The $111,878 award, effective February 15, 2025 through January...
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...
This four-year, $400,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems supports research at the Massachusetts Institute of Technology under the Computer and Information Science and Engineering program. The grant funds the development of new techniques for composing implicit representations to enable machines to perceive and reconstruct 3D scenes in a more generalizable manner. Investigators will explore methods to make representations...
This $600,000 project grant, awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, will support research to develop a new Bayesian diffusion model framework for advanced visual perception and cognition systems. The University of California, San Diego (UCSD) will serve as the primary awardee, with the goal of revisiting the analysis-by-synthesis methodology by integrating generative priors into the learning and inference...
Brown University was awarded a $904,860 Project Grant from the National Science Foundation Division of Computer and Network Systems. The grant is part of the NSF's Computer and Information Science and Engineering program (CFDA 47.070), which supports investigator-initiated research and education in computing, communications, and information science and engineering. Under this award, Brown University will conduct collaborative research titled "COLLABORATIVE RESEARCH: CPS: MEDIUM: CLOSING THE...
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 will develop new techniques for numerical stability analysis in multiview geometry tasks, tools for solving large polynomial systems, and a novel multiview geometry approach integrating curves, surfaces, and differential geometry. These advancements are intended to enable robust, efficient, and reliable 3D reconstruction and spatial understanding from multiview image data, with applications in autonomous systems, robotics, metrology, and entertainment. The project period runs from September 1, 2023 to August 31, 2027.