基于单张图像的4D合成:联合三维几何重建与运动生成 / Joint 3D Geometry Reconstruction and Motion Generation for 4D Synthesis from a Single Image
1️⃣ 一句话总结
这篇论文提出了一种名为MoRe4D的新方法,能够仅凭一张静态图片,就同时生成物体的三维形状和逼真的动态效果,创造出连贯且细节丰富的四维(3D+时间)场景。
Generating interactive and dynamic 4D scenes from a single static image remains a core challenge. Most existing generate-then-reconstruct and reconstruct-then-generate methods decouple geometry from motion, causing spatiotemporal inconsistencies and poor generalization. To address these, we extend the reconstruct-then-generate framework to jointly perform Motion generation and geometric Reconstruction for 4D Synthesis (MoRe4D). We first introduce TrajScene-60K, a large-scale dataset of 60,000 video samples with dense point trajectories, addressing the scarcity of high-quality 4D scene data. Based on this, we propose a diffusion-based 4D Scene Trajectory Generator (4D-STraG) to jointly generate geometrically consistent and motion-plausible 4D point trajectories. To leverage single-view priors, we design a depth-guided motion normalization strategy and a motion-aware module for effective geometry and dynamics integration. We then propose a 4D View Synthesis Module (4D-ViSM) to render videos with arbitrary camera trajectories from 4D point track representations. Experiments show that MoRe4D generates high-quality 4D scenes with multi-view consistency and rich dynamic details from a single image. Code: this https URL.
基于单张图像的4D合成:联合三维几何重建与运动生成 / Joint 3D Geometry Reconstruction and Motion Generation for 4D Synthesis from a Single Image
这篇论文提出了一种名为MoRe4D的新方法,能够仅凭一张静态图片,就同时生成物体的三维形状和逼真的动态效果,创造出连贯且细节丰富的四维(3D+时间)场景。
源自 arXiv: 2512.05044