187 citations · 206 across the 4 of their papers we have counts for
5 papers
GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images
Jun Gao, Tianchang Shen, Zian Wang +6
As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of…
EditGAN: High-Precision Semantic Image Editing
Huan Ling, Karsten Kreis, Daiqing Li +3
Generative adversarial networks (GANs) have recently found applications in image editing. However, most GAN based image editing methods often require large scale datasets with sema…
Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization
Daiqing Li, Junlin Yang, Karsten Kreis +2
Training deep networks with limited labeled data while achieving a strong generalization ability is key in the quest to reduce human annotation efforts. This is the goal of semi-su…
Fed-Sim: Federated Simulation for Medical Imaging
Daiqing Li, Amlan Kar, Nishant Ravikumar +2
Labelling data is expensive and time consuming especially for domains such as medical imaging that contain volumetric imaging data and require expert knowledge. Exploiting a larger…
A Face-to-Face Neural Conversation Model
Hang Chu, Daiqing Li, Sanja Fidler
Neural networks have recently become good at engaging in dialog. However, current approaches are based solely on verbal text, lacking the richness of a real face-to-face conversati…