ConsistencyDet: Robust Object Detector with Denoising Paradigm of Consistency Model

arXiv:2404.07773v1 Announce Type: new
Abstract: Object detection, a quintessential task in the realm of perceptual computing, can be tackled using a generative methodology. In the present study, we introduce a novel framework designed to articulate object detection as a denoising diffusion process, which operates on perturbed bounding boxes of annotated entities. This framework, termed ConsistencyDet, leverages an innovative denoising concept known as the Consistency Model. The hallmark of this model is its self-consistency feature, which empowers the model to map …

abstract arxiv computing consistency model cs.cv denoising detection diffusion framework generative methodology novel object paradigm process realm robust study type