10 citations · 17 across the 2 of their papers we have counts for
3 papers
cs.CV2021★ 10 cited
Multimodal Semi-Supervised Learning for 3D Objects
Zhimin Chen, Longlong Jing, Yang Liang +2
In recent years, semi-supervised learning has been widely explored and shows excellent data efficiency for 2D data. There is an emerging need to improve data efficiency for 3D task…
cs.CV2021★ 7 cited
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation
Bing Li, Yuanlue Zhu, Yitong Wang +3
In this paper, we propose a novel framework to translate a portrait photo-face into an anime appearance. Our aim is to synthesize anime-faces which are style-consistent with a give…
cs.CV2020
MVTN: Multi-View Transformation Network for 3D Shape Recognition
Abdullah Hamdi, Silvio Giancola, Bernard Ghanem
Multi-view projection methods have demonstrated their ability to reach state-of-the-art performance on 3D shape recognition. Those methods learn different ways to aggregate informa…