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 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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $300,000 to Temple University to enhance computer vision capabilities through shape configuration learning. The 3-year project aims to develop new deep learning techniques that allow computers to better recognize and comprehend objects as interconnected shapes, rather than just individual parts. This includes improving attention mechanisms to focus on relevant...
This $377,674 CAREER award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to enhance adaptability in multimodal human-robot interaction. The project aims to develop advanced algorithms for understanding human intentions using multimodal data like verbal messages, gestures, and eye gaze. It will also create new learning and planning methods to help robots align their actions with human intentions, as...
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...
This $1,200,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to democratize access to large-scale visual AI models. The research will focus on developing novel learning approaches that reduce the data, computation, and expert knowledge required to create and deploy specialized computer vision applications. Key objectives include enhancing inference efficiency, enabling fast model specialization...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $124,998 to Worcester Polytechnic Institute (WPI) from August 2025 to July 2027. The award supports research to enable robots to learn abstract representations of states and actions from visual and execution data, enhancing their adaptability and autonomy in real-world, unstructured environments. Key research activities include developing methods for...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, supports a research project titled "CAREER: ACTIVE SCENE UNDERSTANDING BY AND FOR ROBOT MANIPULATION" at Stanford University. The $130,000 grant, awarded on October 1, 2023, aims to develop a self-improving robot perception system that leverages manipulation skills for active scene understanding. The key focus is on enabling robots to...
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...
The National Science Foundation awarded a $438,863 Project Grant to the Regents of the University of Minnesota under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The five-year award will support the development of novel computational algorithms to enable robots to visually understand scenes, learn manipulation action sequences, and adapt to different environmental settings for challenging object grasping. Specifically, the Principal Investigator...