3 papers
cs.CV2025
RMLer: Synthesizing Novel Objects across Diverse Categories via Reinforcement Mixing Learning
Jun Li, Zikun Chen, Haibo Chen +2
Novel object synthesis by integrating distinct textual concepts from diverse categories remains a significant challenge in Text-to-Image (T2I) generation. Existing methods often su…
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…
cs.CV2024
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…