MorphoSim: An Interactive, Controllable, and Editable Language-guided 4D World Simulator
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866914076340256768 |
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| author | He, Xuehai Zhou, Shijie Venkateswaran, Thivyanth Zheng, Kaizhi Wan, Ziyu Kadambi, Achuta Wang, Xin Eric |
| author_facet | He, Xuehai Zhou, Shijie Venkateswaran, Thivyanth Zheng, Kaizhi Wan, Ziyu Kadambi, Achuta Wang, Xin Eric |
| contents | World models that support controllable
and editable spatiotemporal environments are valuable
for robotics, enabling scalable training data, repro ducible evaluation, and flexible task design. While
recent text-to-video models generate realistic dynam ics, they are constrained to 2D views and offer limited
interaction. We introduce MorphoSim, a language guided framework that generates 4D scenes with
multi-view consistency and object-level controls. From
natural language instructions, MorphoSim produces
dynamic environments where objects can be directed,
recolored, or removed, and scenes can be observed
from arbitrary viewpoints. The framework integrates
trajectory-guided generation with feature field dis tillation, allowing edits to be applied interactively
without full re-generation. Experiments show that Mor phoSim maintains high scene fidelity while enabling
controllability and editability. The code is available
at https://github.com/eric-ai-lab/Morph4D. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_04390 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MorphoSim: An Interactive, Controllable, and Editable Language-guided 4D World Simulator He, Xuehai Zhou, Shijie Venkateswaran, Thivyanth Zheng, Kaizhi Wan, Ziyu Kadambi, Achuta Wang, Xin Eric Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language World models that support controllable and editable spatiotemporal environments are valuable for robotics, enabling scalable training data, repro ducible evaluation, and flexible task design. While recent text-to-video models generate realistic dynam ics, they are constrained to 2D views and offer limited interaction. We introduce MorphoSim, a language guided framework that generates 4D scenes with multi-view consistency and object-level controls. From natural language instructions, MorphoSim produces dynamic environments where objects can be directed, recolored, or removed, and scenes can be observed from arbitrary viewpoints. The framework integrates trajectory-guided generation with feature field dis tillation, allowing edits to be applied interactively without full re-generation. Experiments show that Mor phoSim maintains high scene fidelity while enabling controllability and editability. The code is available at https://github.com/eric-ai-lab/Morph4D. |
| title | MorphoSim: An Interactive, Controllable, and Editable Language-guided 4D World Simulator |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2510.04390 |