2 citations · 2 across the 5 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
Novel Object Synthesis via Adaptive Text-Image Harmony
Zeren Xiong, Zedong Zhang, Zikun Chen +5
In this paper, we study an object synthesis task that combines an object text with an object image to create a new object image. However, most diffusion models struggle with this t…
TP2O: Creative Text Pair-to-Object Generation using Balance Swap-Sampling
Jun Li, Zedong Zhang, Jian Yang
Generating creative combinatorial objects from two seemingly unrelated object texts is a challenging task in text-to-image synthesis, often hindered by a focus on emulating existin…