Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Guo, Jianzhu"'
Autor:
Guo, Jianzhu, Zhang, Dingyun, Liu, Xiaoqiang, Zhong, Zhizhou, Zhang, Yuan, Wan, Pengfei, Zhang, Di
Portrait Animation aims to synthesize a lifelike video from a single source image, using it as an appearance reference, with motion (i.e., facial expressions and head pose) derived from a driving video, audio, text, or generation. Instead of followin
Externí odkaz:
http://arxiv.org/abs/2407.03168
Unsupervised attributed graph representation learning is challenging since both structural and feature information are required to be represented in the latent space. Existing methods concentrate on learning latent representation via reconstruction t
Externí odkaz:
http://arxiv.org/abs/2104.13048
A standard pipeline of current face recognition frameworks consists of four individual steps: locating a face with a rough bounding box and several fiducial landmarks, aligning the face image using a pre-defined template, extracting representations a
Externí odkaz:
http://arxiv.org/abs/2102.05447
Existing methods of 3D dense face alignment mainly concentrate on accuracy, thus limiting the scope of their practical applications. In this paper, we propose a novel regression framework named 3DDFA-V2 which makes a balance among speed, accuracy and
Externí odkaz:
http://arxiv.org/abs/2009.09960
Long-tailed problem has been an important topic in face recognition task. However, existing methods only concentrate on the long-tailed distribution of classes. Differently, we devote to the long-tailed domain distribution problem, which refers to th
Externí odkaz:
http://arxiv.org/abs/2003.13791
Face recognition systems are usually faced with unseen domains in real-world applications and show unsatisfactory performance due to their poor generalization. For example, a well-trained model on webface data cannot deal with the ID vs. Spot task in
Externí odkaz:
http://arxiv.org/abs/2003.07733
Face anti-spoofing is crucial for the security of face recognition systems. Learning based methods especially deep learning based methods need large-scale training samples to reduce overfitting. However, acquiring spoof data is very expensive since t
Externí odkaz:
http://arxiv.org/abs/1901.00488
In the application of face recognition, eyeglasses could significantly degrade the recognition accuracy. A feasible method is to collect large-scale face images with eyeglasses for training deep learning methods. However, it is difficult to collect t
Externí odkaz:
http://arxiv.org/abs/1806.01196
Publikováno v:
In Neurocomputing 1 December 2022 514:83-93
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.