10 citations · 12 across the 7 of their papers we have counts for
8 papers · 1 filter
AddressVLM: Cross-view Alignment Tuning for Image Address Localization using Large Vision-Language Models
Shixiong Xu, Chenghao Zhang, Lubin Fan +5
Large visual language models (LVLMs) have demonstrated impressive performance in coarse-grained geo-localization at the country or city level, but they struggle with fine-grained s…
Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger
Qi Yang, Chenghao Zhang, Lubin Fan +3
Recent advancements in Large Vision Language Models (LVLMs) have significantly improved performance in Visual Question Answering (VQA) tasks through multimodal Retrieval-Augmented…
A Survey of Low-shot Vision-Language Model Adaptation via Representer Theorem
Kun Ding, Ying Wang, Gaofeng Meng +1
The advent of pre-trained vision-language foundation models has revolutionized the field of zero/few-shot (i.e., low-shot) image recognition. The key challenge to address under the…
Calibrated Cache Model for Few-Shot Vision-Language Model Adaptation
Kun Ding, Qiang Yu, Haojian Zhang +2
Cache-based approaches stand out as both effective and efficient for adapting vision-language models (VLMs). Nonetheless, the existing cache model overlooks three crucial aspects.…
AddressCLIP: Empowering Vision-Language Models for City-wide Image Address Localization
Shixiong Xu, Chenghao Zhang, Lubin Fan +3
In this study, we introduce a new problem raised by social media and photojournalism, named Image Address Localization (IAL), which aims to predict the readable textual address whe…
Enhancing Visual Continual Learning with Language-Guided Supervision
Bolin Ni, Hongbo Zhao, Chenghao Zhang +4
Continual learning (CL) aims to empower models to learn new tasks without forgetting previously acquired knowledge. Most prior works concentrate on the techniques of architectures,…