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cs.CV2024
COIN: Control-Inpainting Diffusion Prior for Human and Camera Motion Estimation
Jiefeng Li, Ye Yuan, Davis Rempe +5
Estimating global human motion from moving cameras is challenging due to the entanglement of human and camera motions. To mitigate the ambiguity, existing methods leverage learned…
cs.CV2024
Generating Human Interaction Motions in Scenes with Text Control
Hongwei Yi, Justus Thies, Michael J. Black +2
We present TeSMo, a method for text-controlled scene-aware motion generation based on denoising diffusion models. Previous text-to-motion methods focus on characters in isolation w…
cs.CV2024
Multi-Track Timeline Control for Text-Driven 3D Human Motion Generation
Mathis Petrovich, Or Litany, Umar Iqbal +4
Recent advances in generative modeling have led to promising progress on synthesizing 3D human motion from text, with methods that can generate character animations from short prom…