19 citations · 23 across the 7 of their papers we have counts for
7 papers
Dynamic Parsing and Updating Natural Language Specification using VLMs for Robust Vision-Language Tracking
Xiao Wang, Liye Jin, Dan Xu +5
Vision-language tracking guided by natural language specifications leverages high-level semantic cues of target objects to substantially boost tracking accuracy and robustness. Exi…
T2I-VeRW: Part-level Fine-grained Perception for Text-to-Image Vehicle Retrieval
Xiao Wang, Ziwen Wang, Weizhe Kong +5
Vehicle Re-identification (Re-ID) aims to retrieve the most similar image to a given query from images captured by non-overlapping cameras. Extending vehicle Re-ID from image-only…
Sign Language Translation using Frame and Event Stream: Benchmark Dataset and Algorithms
Xiao Wang, Yuehang Li, Fuling Wang +5
Accurate sign language understanding serves as a crucial communication channel for individuals with disabilities. Current sign language translation algorithms predominantly rely on…
CXPMRG-Bench: Pre-training and Benchmarking for X-ray Medical Report Generation on CheXpert Plus Dataset
Xiao Wang, Fuling Wang, Yuehang Li +5
X-ray image-based medical report generation (MRG) is a pivotal area in artificial intelligence which can significantly reduce diagnostic burdens and patient wait times. Despite sig…
R2GenCSR: Mining Contextual and Residual Information for LLMs-based Radiology Report Generation
Xiao Wang, Yuehang Li, Fuling Wang +3
Inspired by the tremendous success of Large Language Models (LLMs), existing Radiology report generation methods attempt to leverage large models to achieve better performance. The…
Pre-training on High Definition X-ray Images: An Experimental Study
Xiao Wang, Yuehang Li, Wentao Wu +5
Existing X-ray based pre-trained vision models are usually conducted on a relatively small-scale dataset (less than 500k samples) with limited resolution (e.g., 224 224).…
State Space Model for New-Generation Network Alternative to Transformers: A Survey
Xiao Wang, Shiao Wang, Yuhe Ding +13
In the post-deep learning era, the Transformer architecture has demonstrated its powerful performance across pre-trained big models and various downstream tasks. However, the enorm…