Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Yahia, Haitam Ben"'
Autor:
Yahia, Haitam Ben, Korzhenkov, Denis, Lelekas, Ioannis, Ghodrati, Amir, Habibian, Amirhossein
Video diffusion models have achieved impressive realism and controllability but are limited by high computational demands, restricting their use on mobile devices. This paper introduces the first mobile-optimized video diffusion model. Starting from
Externí odkaz:
http://arxiv.org/abs/2412.07583
Autor:
Li, Shijie, Zanjani, Farhad G., Yahia, Haitam Ben, Asano, Yuki M., Gall, Juergen, Habibian, Amirhossein
Novel View Synthesis (NVS), which tries to produce a realistic image at the target view given source view images and their corresponding poses, is a fundamental problem in 3D Vision. As this task is heavily under-constrained, some recent work, like Z
Externí odkaz:
http://arxiv.org/abs/2312.08892
This paper accelerates video perception, such as semantic segmentation and human pose estimation, by levering cross-frame redundancies. Unlike the existing approaches, which avoid redundant computations by warping the past features using optical-flow
Externí odkaz:
http://arxiv.org/abs/2308.09511
Autor:
Mehta, Dushyant, Skliar, Andrii, Yahia, Haitam Ben, Borse, Shubhankar, Porikli, Fatih, Habibian, Amirhossein, Blankevoort, Tijmen
Though the state-of-the architectures for semantic segmentation, such as HRNet, demonstrate impressive accuracy, the complexity arising from their salient design choices hinders a range of model acceleration tools, and further they make use of operat
Externí odkaz:
http://arxiv.org/abs/2206.08236
This paper aims to accelerate video stream processing, such as object detection and semantic segmentation, by leveraging the temporal redundancies that exist between video frames. Instead of propagating and warping features using motion alignment, su
Externí odkaz:
http://arxiv.org/abs/2203.09594