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FloodDiffusion 2 advances streaming motion generation with efficiency and path control

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced FloodDiffusion 2 (FD2), an advanced framework designed for efficient and controllable streaming motion generation. This new model builds upon its predecessor, FloodDiffusion (FD1), by addressing limitations in efficiency and precise trajectory control. FD2 incorporates Partial Attention for faster inference and training, a Bregman criterion for regression losses to maintain motion quality, and precise path conditioning to guide character movement along desired trajectories. These improvements result in a significant reduction in training computation and denoising time, alongside state-of-the-art performance on benchmarks like SEED and HumanML3D. AI

IMPACT Enhances efficiency and controllability in AI-driven motion generation, potentially impacting animation and robotics.

RANK_REASON The cluster contains a research paper detailing a new model and its technical advancements. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

FloodDiffusion 2 advances streaming motion generation with efficiency and path control

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The cluster contains a research paper detailing a new model and its technical advancements. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Yiyi Cai, Yuhan Wu, Kunhang Li, Tu Fangyuan, Xiangyue Zhang, Qiaoge Li, Zhixiang Wang, Kaipeng Zhang, Haiyang Liu ·

    FloodDiffusion 2: Efficient and Path Controllable Streaming Motion Generation

    arXiv:2609.33167v2 Announce Type: replace Abstract: We present FloodDiffusion 2 (FD2), an efficient and controllable framework that builds upon FloodDiffusion (FD1), a state-of-the-art streaming motion generation model. While FD1 produces plausible motion, it suffers from low eff…

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