36 citations · 100 across the 13 of their papers we have counts for
13 papers
Highly Efficient Natural Image Matting
Yijie Zhong, Bo Li, Lv Tang +2
Over the last few years, deep learning based approaches have achieved outstanding improvements in natural image matting. However, there are still two drawbacks that impede the wide…
AniFormer: Data-driven 3D Animation with Transformer
Haoyu Chen, Hao Tang, Nicu Sebe +1
We present a novel task, i.e., animating a target 3D object through the motion of a raw driving sequence. In previous works, extra auxiliary correlations between source and target…
Multi-Sample based Contrastive Loss for Top-k Recommendation
Hao Tang, Guoshuai Zhao, Yuxia Wu +1
The top-k recommendation is a fundamental task in recommendation systems which is generally learned by comparing positive and negative pairs. The Contrastive Loss (CL) is the key i…
Layout-to-Image Translation with Double Pooling Generative Adversarial Networks
Hao Tang, Nicu Sebe
In this paper, we address the task of layout-to-image translation, which aims to translate an input semantic layout to a realistic image. One open challenge widely observed in exis…
Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer
Haoyu Chen, Hao Tang, Henglin Shi +3
With the strength of deep generative models, 3D pose transfer regains intensive research interests in recent years. Existing methods mainly rely on a variety of constraints to achi…
Total Generate: Cycle in Cycle Generative Adversarial Networks for Generating Human Faces, Hands, Bodies, and Natural Scenes
Hao Tang, Nicu Sebe
We propose a novel and unified Cycle in Cycle Generative Adversarial Network (C2GAN) for generating human faces, hands, bodies, and natural scenes. Our proposed C2GAN is a cross-mo…