7 papers
Dual-Branch Cross-Projection Debiasing through Diffusion-based Disentanglement
Xiangqian Zhao, Xinyang Jiang, Zhipeng Xu +5
Foundation models trained on biased datasets often rely on spurious correlations between target labels and non-causal attributes, resulting in poor generalization on minority group…
Reasoning-Driven Multimodal LLM for Domain Generalization
Zhipeng Xu, Zilong Wang, Xinyang Jiang +3
This paper addresses the domain generalization (DG) problem in deep learning. While most DG methods focus on enforcing visual feature invariance, we leverage the reasoning capabili…
Hierarchical Identity Learning for Unsupervised Visible-Infrared Person Re-Identification
Haonan Shi, Yubin Wang, De Cheng +3
Unsupervised visible-infrared person re-identification (USVI-ReID) aims to learn modality-invariant image features from unlabeled cross-modal person datasets by reducing the modali…
Harnessing Textual Semantic Priors for Knowledge Transfer and Refinement in CLIP-Driven Continual Learning
Lingfeng He, De Cheng, Di Xu +2
Continual learning (CL) aims to equip models with the ability to learn from a stream of tasks without forgetting previous knowledge. With the progress of vision-language models lik…
EKPC: Elastic Knowledge Preservation and Compensation for Class-Incremental Learning
Huaijie Wang, De Cheng, Lingfeng He +4
Class-Incremental Learning (CIL) aims to enable AI models to continuously learn from sequentially arriving data of different classes over time while retaining previously acquired k…
Semantic-Aligned Learning with Collaborative Refinement for Unsupervised VI-ReID
De Cheng, Lingfeng He, Nannan Wang +2
Unsupervised visible-infrared person re-identification (USL-VI-ReID) seeks to match pedestrian images of the same individual across different modalities without human annotations f…