6 papers · 1 filter
Making Image Editing Easier via Adaptive Task Reformulation with Agentic Executions
Bo Zhao, Kairui Guo, Runnan Du +6
Instruction guided image editing has advanced substantially with recent generative models, yet it still fails to produce reliable results across many seemingly simple cases. We obs…
TexEditor: Structure-Preserving Text-Driven Texture Editing
Bo Zhao, Yihang Liu, Chenfeng Zhang +3
Text-guided texture editing aims to modify object appearance while preserving the underlying geometric structure. However, our empirical analysis reveals that even SOTA editing mod…
Interp3D: Correspondence-aware Interpolation for Generative Textured 3D Morphing
Xiaolu Liu, Yicong Li, Qiyuan He +4
Textured 3D morphing seeks to generate smooth and plausible transitions between two 3D assets, preserving both structural coherence and fine-grained appearance. This ability is cru…
SEGA: A Stepwise Evolution Paradigm for Content-Aware Layout Generation with Design Prior
Haoran Wang, Bo Zhao, Jinghui Wang +5
In this paper, we study the content-aware layout generation problem, which aims to automatically generate layouts that are harmonious with a given background image. Existing method…
MoTe: Learning Motion-Text Diffusion Model for Multiple Generation Tasks
Yiming Wu, Wei Ji, Kecheng Zheng +2
Recently, human motion analysis has experienced great improvement due to inspiring generative models such as the denoising diffusion model and large language model. While the exist…
Towards Small Object Editing: A Benchmark Dataset and A Training-Free Approach
Qihe Pan, Zhen Zhao, Zicheng Wang +5
A plethora of text-guided image editing methods has recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models especially St…