32 citations · 51 across the 5 of their papers we have counts for
5 papers
Intelligent Grimm -- Open-ended Visual Storytelling via Latent Diffusion Models
Chang Liu, Haoning Wu, Yujie Zhong +3
Generative models have recently exhibited exceptional capabilities in text-to-image generation, but still struggle to generate image sequences coherently. In this work, we focus on…
UATVR: Uncertainty-Adaptive Text-Video Retrieval
Bo Fang, Wenhao Wu, Chang Liu +6
With the explosive growth of web videos and emerging large-scale vision-language pre-training models, e.g., CLIP, retrieving videos of interest with text instructions has attracted…
CounTR: Transformer-based Generalised Visual Counting
Chang Liu, Yujie Zhong, Andrew Zisserman +1
In this paper, we consider the problem of generalised visual object counting, with the goal of developing a computational model for counting the number of objects from arbitrary se…
Vision-Language Transformer and Query Generation for Referring Segmentation
Henghui Ding, Chang Liu, Suchen Wang +1
In this work, we address the challenging task of referring segmentation. The query expression in referring segmentation typically indicates the target object by describing its rela…
Towards Enhancing Fine-grained Details for Image Matting
Chang Liu, Henghui Ding, Xudong Jiang
In recent years, deep natural image matting has been rapidly evolved by extracting high-level contextual features into the model. However, most current methods still have difficult…