IdGlow is a progressive two-stage diffusion framework that uses task-adaptive timestep scheduling, temporal gating, VLM prompt synthesis, and group-level DPO to balance identity preservation and scene coherence in multi-subject image generation.
Advances in Neural Information Processing Systems (NeurIPS) (2022) 8, 10
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
IdGlow: Dynamic Identity Modulation for Multi-Subject Generation
IdGlow is a progressive two-stage diffusion framework that uses task-adaptive timestep scheduling, temporal gating, VLM prompt synthesis, and group-level DPO to balance identity preservation and scene coherence in multi-subject image generation.