6 papers · 1 filter
Aligned Stable Inpainting: Mitigating Unwanted Object Insertion and Preserving Color Consistency
Yikai Wang, Junqiu Yu, Chenjie Cao +2
Generative image inpainting can produce realistic results even with large, irregular masks, but existing methods still suffer from two common problems: (1) Unwanted object insertio…
Towards Enhanced Image Inpainting: Mitigating Unwanted Object Insertion and Preserving Color Consistency
Yikai Wang, Chenjie Cao, Junqiu Yu +3
Recent advances in image inpainting increasingly use generative models to handle large irregular masks. However, these models can create unrealistic inpainted images due to two mai…
AnyRefill: A Unified, Data-Efficient Framework for Left-Prompt-Guided Vision Tasks
Ming Xie, Chenjie Cao, Yunuo Cai +3
In this paper, we present a novel Left-Prompt-Guided (LPG) paradigm to address a diverse range of reference-based vision tasks. Inspired by the human creative process, we reformula…
Repositioning the Subject within Image
Yikai Wang, Chenjie Cao, Ke Fan +4
Current image manipulation primarily centers on static manipulation, such as replacing specific regions within an image or altering its overall style. In this paper, we introduce a…
Improving Neural Surface Reconstruction with Feature Priors from Multi-View Image
Xinlin Ren, Chenjie Cao, Yanwei Fu +1
Recent advancements in Neural Surface Reconstruction (NSR) have significantly improved multi-view reconstruction when coupled with volume rendering. However, relying solely on phot…
LeftRefill: Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion Model
Chenjie Cao, Yunuo Cai, Qiaole Dong +2
This paper introduces LeftRefill, an innovative approach to efficiently harness large Text-to-Image (T2I) diffusion models for reference-guided image synthesis. As the name implies…