1 code implementation • 13 Mar 2023 • Hannah Kirkland, Sanjeev J. Koppal
We propose a novel design for privacy preservation, where the imagery is stored in quantum states.
1 code implementation • CVPR 2023 • Brevin Tilmon, Zhanghao Sun, Sanjeev J. Koppal, Yicheng Wu, Georgios Evangelidis, Ramzi Zahreddine, Gurunandan Krishnan, Sizhuo Ma, Jian Wang
Active depth sensing achieves robust depth estimation but is usually limited by the sensing range.
1 code implementation • ICCV 2021 • Brevin Tilmon, Sanjeev J. Koppal
Most monocular depth sensing methods use conventionally captured images that are created without considering scene content.
no code implementations • 21 Mar 2020 • Francesco Pittaluga, Zaid Tasneem, Justin Folden, Brevin Tilmon, Ayan Chakrabarti, Sanjeev J. Koppal
We present a proof-of-concept LIDAR design that allows adaptive real-time measurements according to dynamically specified measurement patterns.
no code implementations • CVPR 2019 • Francesco Pittaluga, Sanjeev J. Koppal, Sing Bing Kang, Sudipta N. Sinha
We present a privacy attack that reconstructs color images of the scene from the point cloud.
no code implementations • 14 Feb 2018 • Francesco Pittaluga, Sanjeev J. Koppal, Ayan Chakrabarti
We present a framework to learn privacy-preserving encodings of images that inhibit inference of chosen private attributes, while allowing recovery of other desirable information.
no code implementations • CVPR 2015 • Francesco Pittaluga, Sanjeev J. Koppal
Most privacy preserving algorithms for computer vision are applied after image/video data has been captured.