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cs.CV2025
VMDiff: Visual Mixing Diffusion for Limitless Cross-Object Synthesis
Zeren Xiong, Yue Yu, Zedong Zhang +3
Creating novel images by fusing visual cues from multiple sources is a fundamental yet underexplored problem in image-to-image generation, with broad applications in artistic creat…
cs.CV2025★ 2 cited
AGSwap: Overcoming Category Boundaries in Object Fusion via Adaptive Group Swapping
Zedong Zhang, Ying Tai, Jianjun Qian +2
Fusing cross-category objects to a single coherent object has gained increasing attention in text-to-image (T2I) generation due to its broad applications in virtual reality, digita…
cs.CV2025
Category-Aware 3D Object Composition with Disentangled Texture and Shape Multi-view Diffusion
Zeren Xiong, Zikun Chen, Zedong Zhang +4
In this paper, we tackle a new task of 3D object synthesis, where a 3D model is composited with another object category to create a novel 3D model. However, most existing text/imag…