35 citations · 43 across the 11 of their papers we have counts for
9 papers · 1 filter
See More, Match Better: Multi-Source Feature Fusion for Two-View Correspondence Learning
Xiaojie Li, Xin Jiang, Luanyuan Dai +3
Two-view correspondence learning aims to distinguish true correspondences (inliers) from false ones (outliers) in image pairs by leveraging their underlying differences. Existing m…
DreamVAR: Taming Reinforced Visual Autoregressive Model for High-Fidelity Subject-Driven Image Generation
Xin Jiang, Jingwen Chen, Yehao Li +5
Recent advances in subject-driven image generation using diffusion models have attracted considerable attention for their remarkable capabilities in producing high-quality images.…
Fine-grained Image Retrieval via Dual-Vision Adaptation
Xin Jiang, Meiqi Cao, Hao Tang +2
Fine-Grained Image Retrieval~(FGIR) faces challenges in learning discriminative visual representations to retrieve images with similar fine-grained features. Current leading FGIR s…
OT-DETECTOR: Delving into Optimal Transport for Zero-shot Out-of-Distribution Detection
Yu Liu, Hao Tang, Haiqi Zhang +2
Out-of-distribution (OOD) detection is crucial for ensuring the reliability and safety of machine learning models in real-world applications. While zero-shot OOD detection, which r…
IMAGDressing-v1: Customizable Virtual Dressing
Fei Shen, Xin Jiang, Xin He +5
Latest advances have achieved realistic virtual try-on (VTON) through localized garment inpainting using latent diffusion models, significantly enhancing consumers' online shopping…
DVF: Advancing Robust and Accurate Fine-Grained Image Retrieval with Retrieval Guidelines
Xin Jiang, Hao Tang, Rui Yan +2
Fine-grained image retrieval (FGIR) is to learn visual representations that distinguish visually similar objects while maintaining generalization. Existing methods propose to gener…
Learning Contrastive Self-Distillation for Ultra-Fine-Grained Visual Categorization Targeting Limited Samples
Ziye Fang, Xin Jiang, Hao Tang +1
In the field of intelligent multimedia analysis, ultra-fine-grained visual categorization (Ultra-FGVC) plays a vital role in distinguishing intricate subcategories within broader c…
Delving into Multimodal Prompting for Fine-grained Visual Classification
Xin Jiang, Hao Tang, Junyao Gao +3
Fine-grained visual classification (FGVC) involves categorizing fine subdivisions within a broader category, which poses challenges due to subtle inter-class discrepancies and larg…
DiffusionVMR: Diffusion Model for Joint Video Moment Retrieval and Highlight Detection
Henghao Zhao, Kevin Qinghong Lin, Rui Yan +1
Video moment retrieval and highlight detection have received attention in the current era of video content proliferation, aiming to localize moments and estimate clip relevances ba…