activity
20212024
most citedMinerU: An Open-Source Solution for Precise Document Content Extraction

19 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV202419 cited

MinerU: An Open-Source Solution for Precise Document Content Extraction

Bin Wang, Chao Xu, Xiaomeng Zhao +15

Document content analysis has been a crucial research area in computer vision. Despite significant advancements in methods such as OCR, layout detection, and formula recognition, e…

cs.CV20222 cited

Instance-aware Model Ensemble With Distillation For Unsupervised Domain Adaptation

Weimin Wu, Jiayuan Fan, Tao Chen +3

The linear ensemble based strategy, i.e., averaging ensemble, has been proposed to improve the performance in unsupervised domain adaptation tasks. However, a typical UDA task is u…

cs.CV2022

Curriculum-style Local-to-global Adaptation for Cross-domain Remote Sensing Image Segmentation

Bo Zhang, Tao Chen, Bin Wang

Although domain adaptation has been extensively studied in natural image-based segmentation task, the research on cross-domain segmentation for very high resolution (VHR) remote se…

cs.CV2021

Densely Semantic Enhancement for Domain Adaptive Region-free Detectors

Bo Zhang, Tao Chen, Bin Wang +3

Unsupervised domain adaptive object detection aims to adapt a well-trained detector from its original source domain with rich labeled data to a new target domain with unlabeled dat…

cs.CV20214 cited

Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification

Yike Wu, Bo Zhang, Gang Yu +4

The goal of few-shot fine-grained image classification is to recognize rarely seen fine-grained objects in the query set, given only a few samples of this class in the support set.…