40 citations · 71 across the 15 of their papers we have counts for
14 papers · 1 filter
Image Inpainting via Iteratively Decoupled Probabilistic Modeling
Wenbo Li, Xin Yu, Kun Zhou +3
Generative adversarial networks (GANs) have made great success in image inpainting yet still have difficulties tackling large missing regions. In contrast, iterative probabilistic…
High-Quality Entity Segmentation
Lu Qi, Jason Kuen, Weidong Guo +5
Dense image segmentation tasks e.g., semantic, panoptic) are useful for image editing, but existing methods can hardly generalize well in an in-the-wild setting where there are unr…
3D-FM GAN: Towards 3D-Controllable Face Manipulation
Yuchen Liu, Zhixin Shu, Yijun Li +3
3D-controllable portrait synthesis has significantly advanced, thanks to breakthroughs in generative adversarial networks (GANs). However, it is still challenging to manipulate exi…
Text-to-Image Generation via Implicit Visual Guidance and Hypernetwork
Xin Yuan, Zhe Lin, Jason Kuen +2
We develop an approach for text-to-image generation that embraces additional retrieval images, driven by a combination of implicit visual guidance loss and generative objectives. U…
HyperNST: Hyper-Networks for Neural Style Transfer
Dan Ruta, Andrew Gilbert, Saeid Motiian +3
We present HyperNST; a neural style transfer (NST) technique for the artistic stylization of images, based on Hyper-networks and the StyleGAN2 architecture. Our contribution is a n…
Inpainting at Modern Camera Resolution by Guided PatchMatch with Auto-Curation
Lingzhi Zhang, Connelly Barnes, Kevin Wampler +4
Recently, deep models have established SOTA performance for low-resolution image inpainting, but they lack fidelity at resolutions associated with modern cameras such as 4K or more…