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Found 7 papers, 2 papers with code
ConsistencyDet: A Robust Object Detector with a Denoising Paradigm of Consistency Model
In the present study, we introduce a novel framework designed to articulate object detection as a denoising diffusion process, which operates on the perturbed bounding boxes of annotated entities.
Peer is Your Pillar: A Data-unbalanced Conditional GANs for Few-shot Image Generation
Few-shot image generation aims to train generative models using a small number of training images.
Shape-centered Representation Learning for Visible-Infrared Person Re-identification
One pertains to the dependence on auxiliary models for shape feature extraction in the inference phase, along with the errors in generated infrared shapes due to the intrinsic modality disparity.
Ranking-based Adaptive Query Generation for DETRs in Crowded Pedestrian Detection
Moreover, to train the rank prediction head better, we propose Soft Gradient L1 Loss.
PRO-Face S: Privacy-preserving Reversible Obfuscation of Face Images via Secure Flow
This paper proposes a novel paradigm for facial privacy protection that unifies multiple characteristics including anonymity, diversity, reversibility and security within a single lightweight framework.
Selecting Learnable Training Samples is All DETRs Need in Crowded Pedestrian Detection
However, in crowded pedestrian detection, the performance of DETRs is still unsatisfactory due to the inappropriate sample selection method which results in more false positives.
Contextual Learning in Fourier Complex Field for VHR Remote Sensing Images
By stacking various layers of CSA blocks, we propose the Fourier Complex Transformer (FCT) model to learn global contextual information from VHR aerial images following the hierarchical manners.
