32 citations · 100 across the 20 of their papers we have counts for
8 papers · 1 filter
DSText V2: A Comprehensive Video Text Spotting Dataset for Dense and Small Text
Weijia Wu, Yiming Zhang, Yefei He +4
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…
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…
Dual Grained Quantization: Efficient Fine-Grained Quantization for LLM
Luoming Zhang, Wen Fei, Weijia Wu +3
Large Language Models (LLMs) pose significant hardware challenges related to memory requirements and computational ability. There are two mainstream quantization schemes for LLMs:…
EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models
Yefei He, Jing Liu, Weijia Wu +2
Diffusion models have demonstrated remarkable capabilities in image synthesis and related generative tasks. Nevertheless, their practicality for real-world applications is constrai…
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…
PTQD: Accurate Post-Training Quantization for Diffusion Models
Yefei He, Luping Liu, Jing Liu +3
Diffusion models have recently dominated image synthesis tasks. However, the iterative denoising process is expensive in computations at inference time, making diffusion models les…
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,…