Zobrazeno 1 - 10
of 1 213
pro vyhledávání: '"Leonidas J"'
Autor:
George Ntoulas, Charalampos Brakatselos, Gerasimos Nakas, Michail-Zois Asprogerakas, Foteini Delis, Leonidas J. Leontiadis, George Trompoukis, Costas Papatheodoropoulos, Dimitrios Gkikas, Dimitrios Valakos, Giannis Vatsellas, Panagiotis K. Politis, Alexia Polissidis, Katerina Antoniou
Publikováno v:
Translational Psychiatry, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Fragile X syndrome (FXS) is the most common cause of inherited intellectual disabilities and the most prevalent monogenic cause of autism. Although the knockout (KO) of the Fmr1 gene homolog in mice is primarily used for elucidating the neur
Externí odkaz:
https://doaj.org/article/35d64c5f4487448394be49984b01007d
Autor:
Leonidas J. Leontiadis, George Trompoukis, Giota Tsotsokou, Athina Miliou, Panagiotis Felemegkas, Costas Papatheodoropoulos
Publikováno v:
Frontiers in Cellular Neuroscience, Vol 17 (2023)
Fragile X syndrome (FXS) is a genetic neurodevelopmental disorder characterized by intellectual disability and is related to autism. FXS is caused by mutations of the fragile X messenger ribonucleoprotein 1 gene (Fmr1) and is associated with alterati
Externí odkaz:
https://doaj.org/article/786956d116b74a478e4b3d319d979b93
Autor:
Leonidas J. Leontiadis, George Trompoukis, Panagiotis Felemegkas, Giota Tsotsokou, Athina Miliou, Costas Papatheodoropoulos
Publikováno v:
Brain Sciences, Vol 13, Iss 11, p 1598 (2023)
A common neurobiological mechanism in several neurodevelopmental disorders, including fragile X syndrome (FXS), is alterations in the balance between excitation and inhibition in the brain. It is thought that in the hippocampus, as in other brain reg
Externí odkaz:
https://doaj.org/article/c5ee548d57ef4eb6a3829fbcd0a60070
Autor:
Nakayama, Kiyohiro, Ackermann, Jan, Kesdogan, Timur Levent, Zheng, Yang, Korosteleva, Maria, Sorkine-Hornung, Olga, Guibas, Leonidas J., Yang, Guandao, Wetzstein, Gordon
Apparel is essential to human life, offering protection, mirroring cultural identities, and showcasing personal style. Yet, the creation of garments remains a time-consuming process, largely due to the manual work involved in designing them. To simpl
Externí odkaz:
http://arxiv.org/abs/2412.03937
Large-scale vision foundation models such as Segment Anything (SAM) demonstrate impressive performance in zero-shot image segmentation at multiple levels of granularity. However, these zero-shot predictions are rarely 3D-consistent. As the camera vie
Externí odkaz:
http://arxiv.org/abs/2405.19678
Autor:
Jiahui Huang, Jun Gao, Vignesh Ganapathi-Subramanian, Hao Su, Yin Liu, Chengcheng Tang, Leonidas J. Guibas
Publikováno v:
Computational Visual Media, Vol 4, Iss 4, Pp 385-397 (2018)
Abstract The perception of the visual world through basic building blocks, such as cubes, spheres, and cones, gives human beings a parsimonious understanding of the visual world. Thus, efforts to find primitive-based geometric interpretations of visu
Externí odkaz:
https://doaj.org/article/712691899e18471fba421d995aa4e38c
Autor:
Pan, Boxiao, Xu, Zhan, Huang, Chun-Hao Paul, Singh, Krishna Kumar, Zhou, Yang, Guibas, Leonidas J., Yang, Jimei
Generating video background that tailors to foreground subject motion is an important problem for the movie industry and visual effects community. This task involves synthesizing background that aligns with the motion and appearance of the foreground
Externí odkaz:
http://arxiv.org/abs/2401.10822
Neural radiance fields (NeRFs) have gained popularity with multiple works showing promising results across various applications. However, to the best of our knowledge, existing works do not explicitly model the distribution of training camera poses,
Externí odkaz:
http://arxiv.org/abs/2401.08140
Given the difficulty of manually annotating motion in video, the current best motion estimation methods are trained with synthetic data, and therefore struggle somewhat due to a train/test gap. Self-supervised methods hold the promise of training dir
Externí odkaz:
http://arxiv.org/abs/2401.00850
Publikováno v:
Proceedings of the 40th International Conference on Machine Learning, PMLR 202:36958-36977, 2023
Some extremely low-dimensional yet crucial geometric eigen-lengths often determine the success of some geometric tasks. For example, the height of an object is important to measure to check if it can fit between the shelves of a cabinet, while the wi
Externí odkaz:
http://arxiv.org/abs/2312.15610