← Search

Shijuan Huang

5 accepted papers

2026

Dual-stream Relation-modeling Disentanglement for Cloth-Changing Person Re-Identification

AAAI 2026technical

Cloth-changing person re-identification (CC-ReID) aims to identify individuals across non-overlapping cameras despite clothing variations. Existing methods are often constrained by two primary limitations: approaches using auxiliary modalities typically rely on a single specific cue, limiting their

Cited by 0SourcePDFScholar
2025

Autoregressive Motion Generation with Gaussian Mixture-Guided Latent Sampling

NeurIPS 2025poster

Existing efforts in motion synthesis typically utilize either generative transformers with discrete representations or diffusion models with continuous representations. However, the discretization process in generative transformers can introduce motion errors, while the sampling process in diffusion…

Cited by 0SourceScholar
2025

Detecting Adversarial Data Using Perturbation Forgery

CVPR 2025poster

As a defense strategy against adversarial attacks, adversarial detection aims to identify and filter out adversarial data from the data flow based on discrepancies in distribution and noise patterns between natural and adversarial data. Although previous detection methods achieve high performance in…

2025

Exploring the Potential of Large Vision-Language Models for Unsupervised Text-Based Person Retrieval

AAAI 2025technical

The aim of text-based person retrieval is to identify pedestrians using natural language descriptions within a large-scale image gallery. Traditional methods rely heavily on manually annotated image-text pairs, which are resource-intensive to obtain. With the emergence of Large Vision-Language Model…

Cited by 0SourcePDFScholar
2024

Cross-modal Generation and Alignment via Attribute-guided Prompt for Unsupervised Text-based Person Retrieval

IJCAI 2024poster

Text-based Person Search aims to retrieve a specified person using a given text query. Current methods predominantly rely on paired labeled image-text data to train the cross-modality retrieval model, necessitating laborious and time-consuming labeling. In response to this challenge, we present the…

Cited by 1SourcePDFScholar