Direct 3D-Aware Object Insertion via Decomposed Visual Proxies

Abstract

Object insertion aims to seamlessly composite a reference object into a specified region of a background image. Recent diffusion-based methods achieve high visual quality but formulate insertion as a simple 2D inpainting task, providing no explicit control over the object’s 3D pose and limiting their practical applicability. We propose DIRECT (Decomposed Injection for Reference Composition and Target-integration), a novel framework that integrates interactive pose manipulation with high-fidelity 2D image synthesis to enable precise geometric alignment. Our method decomposes the insertion conditions into three complementary components: appearance guidance capturing visual details from the reference object, geometry guidance derived from the user-adjusted 3D proxy, and target-integration guidance from the background image. We also introduce an automated data construction pipeline to improve training diversity and visual realism. Experiments show that DIRECT outperforms previous methods in both geometric controllability and visual quality.