15 citations · 19 across the 8 of their papers we have counts for
9 papers
SFDATrack: Generalized Source-Free Domain Adaptive Tracking Under Adverse Weather Conditions
Siyuan Yao, Ziqi Wang, Ruiqi Yu +3
Domain adaptive visual object tracking under adverse weather conditions has garnered significant attention in recent years. Despite the impressive performance, existing methods hea…
Ultra-High-Definition Restoration Transformers with Correlation Matching Transformation
Cong Wang, Liyan Wang, Jinshan Pan +4
We propose UHDformer++, a general Transformer-based framework to solve numerous Ultra-High-Definition (UHD) image restoration tasks. UHDformer++ operates across coordinated lea…
Timestep Rescheduling in Diffusion Inversion
Shangquan Sun, Ting Gong, Zhirui Liu +5
Diffusion inversion, which maps images back to the Gaussian latent space of a diffusion model, is a critical task for image reconstruction and editing. While DDIM enables fast dete…
UAGLNet: Uncertainty-Aggregated Global-Local Fusion Network with Cooperative CNN-Transformer for Building Extraction
Siyuan Yao, Dongxiu Liu, Taotao Li +3
Building extraction from remote sensing images is a challenging task due to the complex structure variations of the buildings. Existing methods employ convolutional or self-attenti…
UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions
Siyuan Yao, Rui Zhu, Ziqi Wang +3
Visual object tracking has gained promising progress in past decades. Most of the existing approaches focus on learning target representation in well-conditioned daytime data, whil…
UncTrack: Reliable Visual Object Tracking with Uncertainty-Aware Prototype Memory Network
Siyuan Yao, Yang Guo, Yanyang Yan +2
Transformer-based trackers have achieved promising success and become the dominant tracking paradigm due to their accuracy and efficiency. Despite the substantial progress, most of…
Degradation-Guided One-Step Image Super-Resolution with Diffusion Priors
Aiping Zhang, Zongsheng Yue, Renjing Pei +2
Diffusion-based image super-resolution (SR) methods have achieved remarkable success by leveraging large pre-trained text-to-image diffusion models as priors. However, these method…
DI-Retinex: Digital-Imaging Retinex Theory for Low-Light Image Enhancement
Shangquan Sun, Wenqi Ren, Jingyang Peng +2
Many existing methods for low-light image enhancement (LLIE) based on Retinex theory ignore important factors that affect the validity of this theory in digital imaging, such as no…
How Powerful Potential of Attention on Image Restoration?
Cong Wang, Jinshan Pan, Yeying Jin +5
Transformers have demonstrated their effectiveness in image restoration tasks. Existing Transformer architectures typically comprise two essential components: multi-head self-atten…