7 citations · 12 across the 6 of their papers we have counts for
6 papers
Tuning-Free Latent Diffusion Models for Ultrahigh-Resolution Image Editing
Wanglong Lu, Lingming Su, Kaijie Shi +4
Recent diffusion-based generative models have shown impressive performance in image generation and editing. However, due to memory limitations and the high cost of collecting high-…
A General Implicit Framework for Fast NeRF Composition and Rendering
Xinyu Gao, Ziyi Yang, Yunlu Zhao +3
A variety of Neural Radiance Fields (NeRF) methods have recently achieved remarkable success in high render speed. However, current accelerating methods are specialized and incompa…
3DPortraitGAN: Learning One-Quarter Headshot 3D GANs from a Single-View Portrait Dataset with Diverse Body Poses
Yiqian Wu, Hao Xu, Xiangjun Tang +3
3D-aware face generators are typically trained on 2D real-life face image datasets that primarily consist of near-frontal face data, and as such, they are unable to construct one-q…
GRIG: Few-Shot Generative Residual Image Inpainting
Wanglong Lu, Xianta Jiang, Xiaogang Jin +5
Image inpainting is the task of filling in missing or masked region of an image with semantically meaningful contents. Recent methods have shown significant improvement in dealing…
LPFF: A Portrait Dataset for Face Generators Across Large Poses
Yiqian Wu, Jing Zhang, Hongbo Fu +1
The creation of 2D realistic facial images and 3D face shapes using generative networks has been a hot topic in recent years. Existing face generators exhibit exceptional performan…
Do Inpainting Yourself: Generative Facial Inpainting Guided by Exemplars
Wanglong Lu, Hanli Zhao, Xianta Jiang +5
We present EXE-GAN, a novel exemplar-guided facial inpainting framework using generative adversarial networks. Our approach can not only preserve the quality of the input facial im…