MATE4D: Matrix-Guided Editable 4D Generation from a Single Image
Generative models have rapidly pushed content creation be-yond 2D imagery toward dynamic 3D and 4D scene synthesis.
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Key points
- Yet pro-ducing realistic and temporally stable 4D content from a single image is still difficult because one view provides limited structural cues and weak motion evidence.
- We introduce MATE4D, a framework that converts one input image into editable dynamic 4D content.
- Our method constructs a spatio-temporal multi-view image matrix with text-guided background manipulation, delivering coherent supervision over viewpoint, appear-ance, and motion.
- Experiments on Objaverse-XL and Diffusion4D show that MATE4D outperforms strong baselines in visual quality, effi-ciency, and controllability, supporting practical AR/VR content creation.
Sources (1)
- [1]MATE4D: Matrix-Guided Editable 4D Generation from a Single ImagearXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 03:40 AM
Generative models have rapidly pushed content creation be-yond 2D imagery toward dynamic 3D and 4D scene synthesis.
Yet pro-ducing realistic and temporally stable 4D content from a single image is still difficult because one view provides limited structural cues and weak motion evidence.
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