32 citations · 42 across the 4 of their papers we have counts for
5 papers
F3A-GAN: Facial Flow for Face Animation with Generative Adversarial Networks
Xintian Wu, Qihang Zhang, Yiming Wu +4
Formulated as a conditional generation problem, face animation aims at synthesizing continuous face images from a single source image driven by a set of conditional face motion. Pr…
D3T-GAN: Data-Dependent Domain Transfer GANs for Few-shot Image Generation
Xintian Wu, Huanyu Wang, Yiming Wu +1
As an important and challenging problem, few-shot image generation aims at generating realistic images through training a GAN model given few samples. A typical solution for few-sh…
Compressing Models with Few Samples: Mimicking then Replacing
Huanyu Wang, Junjie Liu, Xin Ma +3
Few-sample compression aims to compress a big redundant model into a small compact one with only few samples. If we fine-tune models with these limited few samples directly, models…
Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion
Peng Sun, Wenhu Zhang, Huanyu Wang +2
RGB-D salient object detection (SOD) is usually formulated as a problem of classification or regression over two modalities, i.e., RGB and depth. Hence, effective RGBD feature mode…
Ultra Fast Structure-aware Deep Lane Detection
Zequn Qin, Huanyu Wang, Xi Li
Modern methods mainly regard lane detection as a problem of pixel-wise segmentation, which is struggling to address the problem of challenging scenarios and speed. Inspired by huma…