7 papers · 1 filter
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…
A Light-Weight Framework for Open-Set Object Detection with Decoupled Feature Alignment in Joint Space
Yonghao He, Hu Su, Haiyong Yu +4
Open-set object detection (OSOD) is highly desirable for robotic manipulation in unstructured environments. However, existing OSOD methods often fail to meet the requirements of ro…
Correlation Matching Transformation Transformers for UHD Image Restoration
Cong Wang, Jinshan Pan, Wei Wang +5
This paper proposes UHDformer, a general Transformer for Ultra-High-Definition (UHD) image restoration. UHDformer contains two learning spaces: (a) learning in high-resolution spac…
Ultra-High-Definition Image Restoration: New Benchmarks and A Dual Interaction Prior-Driven Solution
Liyan Wang, Cong Wang, Jinshan Pan +5
Ultra-High-Definition (UHD) image restoration has acquired remarkable attention due to its practical demand. In this paper, we construct UHD snow and rain benchmarks, named UHD-Sno…
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…
Phrase Grounding-based Style Transfer for Single-Domain Generalized Object Detection
Hao Li, Wei Wang, Cong Wang +4
Single-domain generalized object detection aims to enhance a model's generalizability to multiple unseen target domains using only data from a single source domain during training.…