Zobrazeno 1 - 10
of 18 466
pro vyhledávání: '"P Seitz"'
We study the problem of joint communication and detection of wiretapping on an optical fiber from a quantum perspective. Our system model describes a communication link that is capable of transmitting data under normal operating conditions and raisin
Externí odkaz:
http://arxiv.org/abs/2411.19622
It is a common belief that quantum key distribution systems are the one and only information-theoretically secure physical layer security protocol that enables secure data transmission without a need for the legitimate parties to have any channel kno
Externí odkaz:
http://arxiv.org/abs/2411.10292
Low latency and high data rate performance are essential in wireless communication systems. This paper explores trade-offs between latency and data rates for optical wireless communication. We introduce a latency-optimized model utilizing compound co
Externí odkaz:
http://arxiv.org/abs/2411.10259
This paper describes an efficient algorithm for solving noisy linear inverse problems using pretrained diffusion models. Extending the paradigm of denoising diffusion implicit models (DDIM), we propose constrained diffusion implicit models (CDIM) tha
Externí odkaz:
http://arxiv.org/abs/2411.00359
Autor:
Amjad, Haadia, Goeller, Kilian, Seitz, Steffen, Knoll, Carsten, Bajwa, Naseer, Tetzlaff, Ronald, Malik, Muhammad Imran
Deep learning is actively being used in biometrics to develop efficient identification and verification systems. Handwritten signatures are a common subset of biometric data for authentication purposes. Generative adversarial networks (GANs) learn fr
Externí odkaz:
http://arxiv.org/abs/2410.06041
Given an input painting, we reconstruct a time-lapse video of how it may have been painted. We formulate this as an autoregressive image generation problem, in which an initially blank "canvas" is iteratively updated. The model learns from real artis
Externí odkaz:
http://arxiv.org/abs/2409.20556
Autor:
Li, Chenjun, Yang, Dian, Yao, Shun, Wang, Shuyue, Wu, Ye, Zhang, Le, Li, Qiannuo, Cho, Kang Ik Kevin, Seitz-Holland, Johanna, Ning, Lipeng, Legarreta, Jon Haitz, Rathi, Yogesh, Westin, Carl-Fredrik, O'Donnell, Lauren J., Sochen, Nir A., Pasternak, Ofer, Zhang, Fan
In this study, we developed an Evidence-based Ensemble Neural Network, namely EVENet, for anatomical brain parcellation using diffusion MRI. The key innovation of EVENet is the design of an evidential deep learning framework to quantify predictive un
Externí odkaz:
http://arxiv.org/abs/2409.07020
Autor:
Wang, Xiaojuan, Zhou, Boyang, Curless, Brian, Kemelmacher-Shlizerman, Ira, Holynski, Aleksander, Seitz, Steven M.
We present a method for generating video sequences with coherent motion between a pair of input key frames. We adapt a pretrained large-scale image-to-video diffusion model (originally trained to generate videos moving forward in time from a single i
Externí odkaz:
http://arxiv.org/abs/2408.15239
Autor:
Gao, Alice, Jayakumar, Samyukta, Maniglia, Marcello, Curless, Brian, Kemelmacher-Shlizerman, Ira, Seitz, Aaron R., Seitz, Steven M.
We consider the question of how to best achieve the perception of eye contact when a person is captured by camera and then rendered on a 2D display. For single subjects photographed by a camera, conventional wisdom tells us that looking directly into
Externí odkaz:
http://arxiv.org/abs/2404.17104
Autor:
Biesterfeld, Leon, Vochezer, Mattis T., Kögel, Marco, Zaluzhnyy, Ivan A., Rosebrock, Marina, Klepzig, Lars F., Leis, Wolfgang, Seitz, Michael, Meyer, Jannik C., Lauth, Jannika
Near-infrared emitting colloidal two-dimensional (2D) PbX (X=S, Se) nanoplatelets have emerged as interesting materials with strong size quantisation in the thickness dimension. They act as model systems for efficient charge carrier multiplication an
Externí odkaz:
http://arxiv.org/abs/2406.09223