activity
20172024
most citedMulti-label Image Recognition by Recurrently Discovering Attentional Regions

53 citations · 99 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2024★ 4 cited

Analysis and Benchmarking of Extending Blind Face Image Restoration to Videos

Zhouxia Wang, Jiawei Zhang, Xintao Wang +4

Recent progress in blind face restoration has resulted in producing high-quality restored results for static images. However, efforts to extend these advancements to video scenario…

cs.CV2023★ 2 cited

Diffusion-based Blind Text Image Super-Resolution

Yuzhe Zhang, Jiawei Zhang, Hao Li +4

Recovering degraded low-resolution text images is challenging, especially for Chinese text images with complex strokes and severe degradation in real-world scenarios. Ensuring both…

cs.CV2023★ 1 cited

MotionCtrl: A Unified and Flexible Motion Controller for Video Generation

Zhouxia Wang, Ziyang Yuan, Xintao Wang +4

Motions in a video primarily consist of camera motion, induced by camera movement, and object motion, resulting from object movement. Accurate control of both camera and object mot…

cs.CV2023★ 7 cited

StyleAdapter: A Unified Stylized Image Generation Model

Zhouxia Wang, Xintao Wang, Liangbin Xie +4

This work focuses on generating high-quality images with specific style of reference images and content of provided textual descriptions. Current leading algorithms, i.e., DreamBoo…

cs.CV2023

RestoreFormer++: Towards Real-World Blind Face Restoration from Undegraded Key-Value Pairs

Zhouxia Wang, Jiawei Zhang, Tianshui Chen +2

Blind face restoration aims at recovering high-quality face images from those with unknown degradations. Current algorithms mainly introduce priors to complement high-quality detai…

cs.CV2022★ 2 cited

RestoreFormer: High-Quality Blind Face Restoration from Undegraded Key-Value Pairs

Zhouxia Wang, Jiawei Zhang, Runjian Chen +2

Blind face restoration is to recover a high-quality face image from unknown degradations. As face image contains abundant contextual information, we propose a method, RestoreFormer…