3 citations · 4 across the 4 of their papers we have counts for
4 papers
Cross-modal Proxy Evolving for OOD Detection with Vision-Language Models
Hao Tang, Yu Liu, Shuanglin Yan +3
Reliable zero-shot detection of out-of-distribution (OOD) inputs is critical for deploying vision-language models in open-world settings. However, the lack of labeled negatives in…
Connecting Giants: Synergistic Knowledge Transfer of Large Multimodal Models for Few-Shot Learning
Hao Tang, Shengfeng He, Jing Qin
Few-shot learning (FSL) addresses the challenge of classifying novel classes with limited training samples. While some methods leverage semantic knowledge from smaller-scale models…
Learning with Unreliability: Fast Few-shot Voxel Radiance Fields with Relative Geometric Consistency
Yingjie Xu, Bangzhen Liu, Hao Tang +2
We propose a voxel-based optimization framework, ReVoRF, for few-shot radiance fields that strategically address the unreliability in pseudo novel view synthesis. Our method pivots…
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…