32 citations · 32 across the 2 of their papers we have counts for
5 papers
Continual Learning for Image Segmentation with Dynamic Query
Weijia Wu, Yuzhong Zhao, Zhuang Li +3
Image segmentation based on continual learning exhibits a critical drop of performance, mainly due to catastrophic forgetting and background shift, as they are required to incorpor…
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models
Weijia Wu, Yuzhong Zhao, Hao Chen +6
Current deep networks are very data-hungry and benefit from training on largescale datasets, which are often time-consuming to collect and annotate. By contrast, synthetic data can…
A Large Cross-Modal Video Retrieval Dataset with Reading Comprehension
Weijia Wu, Yuzhong Zhao, Zhuang Li +4
Most existing cross-modal language-to-video retrieval (VR) research focuses on single-modal input from video, i.e., visual representation, while the text is omnipresent in human en…
ICDAR 2023 Video Text Reading Competition for Dense and Small Text
Weijia Wu, Yuzhong Zhao, Zhuang Li +5
Recently, video text detection, tracking, and recognition in natural scenes are becoming very popular in the computer vision community. However, most existing algorithms and benchm…
DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion Models
Weijia Wu, Yuzhong Zhao, Mike Zheng Shou +2
Collecting and annotating images with pixel-wise labels is time-consuming and laborious. In contrast, synthetic data can be freely available using a generative model (e.g., DALL-E,…