110 citations · 454 across the 51 of their papers we have counts for
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Progressive Painterly Image Harmonization from Low-level Styles to High-level Styles
Li Niu, Yan Hong, Junyan Cao +1
Painterly image harmonization aims to harmonize a photographic foreground object on the painterly background. Different from previous auto-encoder based harmonization networks, we…
Painterly Image Harmonization by Learning from Painterly Objects
Li Niu, Junyan Cao, Yan Hong +1
Given a composite image with photographic object and painterly background, painterly image harmonization targets at stylizing the composite object to be compatible with the backgro…
Painterly Image Harmonization via Adversarial Residual Learning
Xudong Wang, Li Niu, Junyan Cao +2
Image compositing plays a vital role in photo editing. After inserting a foreground object into another background image, the composite image may look unnatural and inharmonious. W…
Virtual Accessory Try-On via Keypoint Hallucination
Junhong Gou, Bo Zhang, Li Niu +4
The virtual try-on task refers to fitting the clothes from one image onto another portrait image. In this paper, we focus on virtual accessory try-on, which fits accessory (e.g., g…
Taming the Power of Diffusion Models for High-Quality Virtual Try-On with Appearance Flow
Junhong Gou, Siyu Sun, Jianfu Zhang +3
Virtual try-on is a critical image synthesis task that aims to transfer clothes from one image to another while preserving the details of both humans and clothes. While many existi…
Deep Image Harmonization in Dual Color Spaces
Linfeng Tan, Jiangtong Li, Li Niu +1
Image harmonization is an essential step in image composition that adjusts the appearance of composite foreground to address the inconsistency between foreground and background. Ex…
Painterly Image Harmonization using Diffusion Model
Lingxiao Lu, Jiangtong Li, Junyan Cao +2
Painterly image harmonization aims to insert photographic objects into paintings and obtain artistically coherent composite images. Previous methods for this task mainly rely on in…
Deep Image Harmonization with Learnable Augmentation
Li Niu, Junyan Cao, Wenyan Cong +1
The goal of image harmonization is adjusting the foreground appearance in a composite image to make the whole image harmonious. To construct paired training images, existing datase…
Deep Image Harmonization with Globally Guided Feature Transformation and Relation Distillation
Li Niu, Linfeng Tan, Xinhao Tao +4
Given a composite image, image harmonization aims to adjust the foreground illumination to be consistent with background. Previous methods have explored transforming foreground fea…
WeditGAN: Few-Shot Image Generation via Latent Space Relocation
Yuxuan Duan, Li Niu, Yan Hong +1
In few-shot image generation, directly training GAN models on just a handful of images faces the risk of overfitting. A popular solution is to transfer the models pretrained on lar…
Few-Shot Defect Image Generation via Defect-Aware Feature Manipulation
Yuxuan Duan, Yan Hong, Li Niu +1
The performances of defect inspection have been severely hindered by insufficient defect images in industries, which can be alleviated by generating more samples as data augmentati…