SEIGAN: Towards Compositional Image Generation by Simultaneously Learning to Segment, Enhance, and Inpaint

19 November 2018

Papers citing "SEIGAN: Towards Compositional Image Generation by Simultaneously Learning to Segment, Enhance, and Inpaint"

5 / 5 papers shown

Title
Unsupervised Foreground Extraction via Deep Region Competition Peiyu Yu Sirui Xie Xiaojian Ma Yixin Zhu Ying Nian Wu Song-Chun Zhu OCL 32 42 0 29 Oct 2021
Edge-competing Pathological Liver Vessel Segmentation with Limited Labels Zunlei Feng Zhonghua Wang Xinchao Wang Jing Zhang Lechao Cheng Jie Lei Yuexuan Wang Xiuming Zhang 32 13 0 01 Aug 2021
GaussiGAN: Controllable Image Synthesis with 3D Gaussians from Unposed Silhouettes Youssef A. Mejjati Isa Milefchik Aaron Gokaslan Oliver Wang K. Kim James Tompkin 3DV 3DGS 35 5 0 24 Jun 2021
Synthetic Data for Deep Learning Sergey I. Nikolenko 46 348 0 25 Sep 2019
Emergence of Object Segmentation in Perturbed Generative Models Adam Bielski Paolo Favaro 33 99 0 29 May 2019