Incentive Noise and Structural Prior Infusion for Multi-modal Object Re-Identification
This work proposes a novel framework centered on Positive-Incentive Noise and structured prompt modulation that harnesses task-aware {\pi}-noise, sampled from a distribution conditioned on both visual and text inputs, to perturb global tokens and enable semantics-guided cross-modal compensation.