FatigueFusion fuses fatigue features in latent space using algorithmic, data-driven, and PINN modules to synthesize novel fatigued motions from non-fatigued joint sequences in an end-to-end pipeline.
Motiondreamer: One-to-many motion synthesis with local- ized generative masked transformer
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
MLA-Gen advances text-driven motion synthesis by aligning global motion patterns with fine-grained text semantics and mitigating attention sink effects via new masking techniques.
citing papers explorer
-
FatigueFusion: Latent Space Fusion for Fatigue-Driven Motion Synthesis
FatigueFusion fuses fatigue features in latent space using algorithmic, data-driven, and PINN modules to synthesize novel fatigued motions from non-fatigued joint sequences in an end-to-end pipeline.
-
Exploring Motion-Language Alignment for Text-driven Motion Generation
MLA-Gen advances text-driven motion synthesis by aligning global motion patterns with fine-grained text semantics and mitigating attention sink effects via new masking techniques.