activity
20162024
most citedPhotoswap: Personalized Subject Swapping in Images

7 citations · 16 across the 10 of their papers we have counts for

collaborators

10 papers

cs.HC2024

AI.vs.Clinician: Unveiling Intricate Interactions Between AI and Clinicians through an Open-Access Database

Wanling Gao, Yuan Liu, Zhuoming Yu +21

Artificial Intelligence (AI) plays a crucial role in medical field and has the potential to revolutionize healthcare practices. However, the success of AI models and their impacts…

cs.CV2024

IMPRINT: Generative Object Compositing by Learning Identity-Preserving Representation

Yizhi Song, Zhifei Zhang, Zhe Lin +7

Generative object compositing emerges as a promising new avenue for compositional image editing. However, the requirement of object identity preservation poses a significant challe…

cs.CV20237 cited

Photoswap: Personalized Subject Swapping in Images

Jing Gu, Yilin Wang, Nanxuan Zhao +8

In an era where images and visual content dominate our digital landscape, the ability to manipulate and personalize these images has become a necessity. Envision seamlessly substit…

cs.CV2023

DualVector: Unsupervised Vector Font Synthesis with Dual-Part Representation

Ying-Tian Liu, Zhifei Zhang, Yuan-Chen Guo +3

Automatic generation of fonts can be an important aid to typeface design. Many current approaches regard glyphs as pixelated images, which present artifacts when scaling and inevit…

cs.CV20236 cited

Improving Diffusion Models for Scene Text Editing with Dual Encoders

Jiabao Ji, Guanhua Zhang, Zhaowen Wang +4

Scene text editing is a challenging task that involves modifying or inserting specified texts in an image while maintaining its natural and realistic appearance. Most previous appr…

cs.CV2023

TopNet: Transformer-based Object Placement Network for Image Compositing

Sijie Zhu, Zhe Lin, Scott Cohen +3

We investigate the problem of automatically placing an object into a background image for image compositing. Given a background image and a segmented object, the goal is to train a…