Zheng Gong

Generative Verification: Rethinking the Uncertainty Signal for Active Learning of Object Detection

The verifier is built as a conditional diffusion model whose diffusion target is a label representation rather than an image, and which outperforms output-uncertainty, feature-geometry, perturbation and ensemble criteria, with its largest margins in the early rounds where confident detector errors are most common.