Zobrazeno 1 - 10
of 995
pro vyhledávání: '"Tran,Phong A"'
Autor:
Tran, Phong, Zakharov, Egor, Ho, Long-Nhat, Hu, Liwen, Karmanov, Adilbek, Agarwal, Aviral, Goldwhite, McLean, Venegas, Ariana Bermudez, Tran, Anh Tuan, Li, Hao
We introduce VOODOO XP: a 3D-aware one-shot head reenactment method that can generate highly expressive facial expressions from any input driver video and a single 2D portrait. Our solution is real-time, view-consistent, and can be instantly used wit
Externí odkaz:
http://arxiv.org/abs/2405.16204
This paper presents an innovative framework designed to train an image deblurring algorithm tailored to a specific camera device. This algorithm works by transforming a blurry input image, which is challenging to deblur, into another blurry image tha
Externí odkaz:
http://arxiv.org/abs/2403.16205
The rapid expansion of user medical records across global systems presents not only opportunities but also new challenges in maintaining effective application models that ensure user privacy, controllability, and the ability to commercialize patient
Externí odkaz:
http://arxiv.org/abs/2402.05498
We present a 3D-aware one-shot head reenactment method based on a fully volumetric neural disentanglement framework for source appearance and driver expressions. Our method is real-time and produces high-fidelity and view-consistent output, suitable
Externí odkaz:
http://arxiv.org/abs/2312.04651
Autor:
Nguyen, Cuong N., Tran, Phong, Ho, Lam Si Tung, Dinh, Vu, Tran, Anh T., Hassner, Tal, Nguyen, Cuong V.
We consider transferability estimation, the problem of estimating how well deep learning models transfer from a source to a target task. We focus on regression tasks, which received little previous attention, and propose two simple and computationall
Externí odkaz:
http://arxiv.org/abs/2312.00656
Trajectory prediction plays a vital role in the performance of autonomous driving systems, and prediction accuracy, such as average displacement error (ADE) or final displacement error (FDE), is widely used as a performance metric. However, a signifi
Externí odkaz:
http://arxiv.org/abs/2306.15136
We consider the challenging task of training models for image-to-video deblurring, which aims to recover a sequence of sharp images corresponding to a given blurry image input. A critical issue disturbing the training of an image-to-video model is th
Externí odkaz:
http://arxiv.org/abs/2304.01686
This paper introduces a method to encode the blur operators of an arbitrary dataset of sharp-blur image pairs into a blur kernel space. Assuming the encoded kernel space is close enough to in-the-wild blur operators, we propose an alternating optimiz
Externí odkaz:
http://arxiv.org/abs/2104.00317
The objective of this work is to deblur face videos. We propose a method that tackles this problem from two directions: (1) enhancing the blurry frames, and (2) treating the blurry frames as missing values and estimate them by interpolation. These ap
Externí odkaz:
http://arxiv.org/abs/2103.00871
Publikováno v:
In Journal of Open Innovation: Technology, Market, and Complexity March 2024 10(1)
