14 citations · 43 across the 9 of their papers we have counts for
4 papers
Joint Learning Content and Degradation Aware Feature for Blind Super-Resolution
Yifeng Zhou, Chuming Lin, Donghao Luo +4
To achieve promising results on blind image super-resolution (SR), some attempts leveraged the low resolution (LR) images to predict the kernel and improve the SR performance. Howe…
SeedFormer: Patch Seeds based Point Cloud Completion with Upsample Transformer
Haoran Zhou, Yun Cao, Wenqing Chu +4
Point cloud completion has become increasingly popular among generation tasks of 3D point clouds, as it is a challenging yet indispensable problem to recover the complete shape of…
Prototypical Contrast Adaptation for Domain Adaptive Semantic Segmentation
Zhengkai Jiang, Yuxi Li, Ceyuan Yang +4
Unsupervised Domain Adaptation (UDA) aims to adapt the model trained on the labeled source domain to an unlabeled target domain. In this paper, we present Prototypical Contrast Ada…
LCTR: On Awakening the Local Continuity of Transformer for Weakly Supervised Object Localization
Zhiwei Chen, Changan Wang, Yabiao Wang +6
Weakly supervised object localization (WSOL) aims to learn object localizer solely by using image-level labels. The convolution neural network (CNN) based techniques often result i…