OmniWeaving: Towards Unified Video Generation with Free-form Composition and Reasoning
While proprietary systems such as Seedance-2.0 have achieved remarkable success in omni-capable video generation, open-source alternatives significantly lag behind. Most academic models remain heavily fragmented, and the few existing efforts toward unified video generation still struggle to seamlessly integrate diverse tasks within a single framework. To bridge this gap, we propose OmniWeaving, an omni-level video generation model featuring powerful multimodal composition and reasoning-informed capabilities. By leveraging a massive-scale pretraining dataset that encompasses diverse compositional and reasoning-augmented scenarios, OmniWeaving learns to temporally bind interleaved text, multi-image, and video inputs while acting as an intelligent agent to infer complex user intentions for sophisticated video creation. Furthermore, we introduce IntelligentVBench, the first comprehensive benchmark designed to rigorously assess next-level intelligent unified video generation. Extensive experiments demonstrate that OmniWeaving achieves SoTA performance among open-source unified models. The codes and model will be made publicly available soon. Project Page: https://omniweaving.github.io.
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Kaihang Pan
claimed_verified
2026-03-26T14:58:26.726Z
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kaihangpan
midbee
user
midbee
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Qi Tian
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Jianwei Zhang
claimed_verified
2026-03-27T11:35:16.617Z
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Jian-Wei Zhang
Jarvis73
user
Jarvis73
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Weijie Kong
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Jiangfeng Xiong
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Yanxin Long
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Shixue Zhang
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Haiyi Qiu
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Tan Wang
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Zheqi Lv
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Yue Wu
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Liefeng Bo
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Siliang Tang
69c49a984ae7eef815b9d99f
Zhao Zhong
OmniWeaving: Towards Unified Video Generation with Free-form Composition and Reasoning
While proprietary systems such as Seedance-2.0 have achieved remarkable success in omni-capable video generation, open-source alternatives significantly lag behind. Most academic models remain heavily fragmented, and the few existing efforts toward unified video generation still struggle to seamlessly integrate diverse tasks within a single framework. To bridge this gap, we propose OmniWeaving, an omni-level video generation model featuring powerful multimodal composition and reasoning-informed capabilities. By leveraging a massive-scale pretraining dataset that encompasses diverse compositional and reasoning-augmented scenarios, OmniWeaving learns to temporally bind interleaved text, multi-image, and video inputs while acting as an intelligent agent to infer complex user intentions for sophisticated video creation. Furthermore, we introduce IntelligentVBench, the first comprehensive benchmark designed to rigorously assess next-level intelligent unified video generation. Extensive experiments demonstrate that OmniWeaving achieves SoTA performance among open-source unified models. The codes and model will be made publicly available soon. Project Page: https://omniweaving.github.io.
OmniWeaving is an open-source video generation model that unifies multimodal inputs and complex reasoning capabilities through large-scale pretraining and intelligent agent inference.
video generation multimodal composition reasoning-informed capabilities pretraining dataset temporal binding intelligent agent unified video generation IntelligentVBench SoTA performance