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FLAME: Free-Form Language-Based Motion Synthesis & Editing

AAAI 2023 · Video › Video generation · approach: Text-to-motion diffusion · 139 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace TEMOS with FLAMEtext-to-motion generation · HumanML3DmCLIP: 0.254 -> 0.297Helped
replace TEMOS with FLAMEtext-to-motion generation · HumanML3DFD: 49.142 -> 21.152Helped
replace TEMOS with FLAMEtext-to-motion generation · BABELR-Precision Top-1: 0.786 -> 0.888Helped
replace TEMOS with FLAMEtext-to-motion generation · KITAVE mean global: 0.448 -> 0.500Hurt
replace TEMOS with FLAMEtext-to-motion generation · HumanML3DJoint Diversity: 0.017 -> 0.072Helped
add motion-length token (ablation)FLAME self-attention architecture · HumanML3DmCLIP: 0.239 -> 0.239No clear effect
add motion-length token (ablation)FLAME self-attention architecture · HumanML3DFD: 60.142 -> 59.254Helped
add cross-attention using full language tokens (ablation)FLAME with motion-length token · HumanML3DmCLIP: 0.239 -> 0.290Helped
add cross-attention using full language tokens (ablation)FLAME with motion-length token · HumanML3DFD: 59.254 -> 27.157Helped
freeze the pretrained language model (ablation)FLAME with cross-attention · HumanML3DR-Precision Top-1: 0.439 -> 0.513Helped
freeze the pretrained language model (ablation)FLAME with cross-attention · HumanML3DFD: 27.157 -> 21.152Helped
reduce sampling steps from 1,000 to 5 (ablation)FLAME trained with T=1000 · motion samplingTime Elapsed (s): 32.81 -> 0.72Helped

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