most citedRethinking the Reference-based Distinctive Image Captioning

22 citations · 26 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Aligning Medical Images with General Knowledge from Large Language Models

Xiao Fang, Yi Lin, Dong Zhang +2

Pre-trained large vision-language models (VLMs) like CLIP have revolutionized visual representation learning using natural language as supervisions, and demonstrated promising gene…

cs.CV20234 cited

Rethinking Boundary Detection in Deep Learning Models for Medical Image Segmentation

Yi Lin, Dong Zhang, Xiao Fang +3

Medical image segmentation is a fundamental task in the community of medical image analysis. In this paper, a novel network architecture, referred to as Convolution, Transformer, a…

cs.CV2023

Coupling Global Context and Local Contents for Weakly-Supervised Semantic Segmentation

Chunyan Wang, Dong Zhang, Liyan Zhang +1

Thanks to the advantages of the friendly annotations and the satisfactory performance, Weakly-Supervised Semantic Segmentation (WSSS) approaches have been extensively studied. Rece…

cs.CV2023

Semantic Scene Completion with Cleaner Self

Fengyun Wang, Dong Zhang, Hanwang Zhang +2

Semantic Scene Completion (SSC) transforms an image of single-view depth and/or RGB 2D pixels into 3D voxels, each of whose semantic labels are predicted. SSC is a well-known ill-p…

cs.CV202222 cited

Rethinking the Reference-based Distinctive Image Captioning

Yangjun Mao, Long Chen, Zhihong Jiang +4

Distinctive Image Captioning (DIC) -- generating distinctive captions that describe the unique details of a target image -- has received considerable attention over the last few ye…