2 citations · 8 across the 15 of their papers we have counts for
7 papers
Contrast, Stylize and Adapt: Unsupervised Contrastive Learning Framework for Domain Adaptive Semantic Segmentation
Tianyu Li, Subhankar Roy, Huayi Zhou +2
To overcome the domain gap between synthetic and real-world datasets, unsupervised domain adaptation methods have been proposed for semantic segmentation. Majority of the previous…
Ultra-High Resolution Segmentation with Ultra-Rich Context: A Novel Benchmark
Deyi Ji, Feng Zhao, Hongtao Lu +2
With the increasing interest and rapid development of methods for Ultra-High Resolution (UHR) segmentation, a large-scale benchmark covering a wide range of scenes with full fine-g…
Degradation-Guided Meta-Restoration Network for Blind Super-Resolution
Fuzhi Yang, Huan Yang, Yanhong Zeng +2
Blind super-resolution (SR) aims to recover high-quality visual textures from a low-resolution (LR) image, which is usually degraded by down-sampling blur kernels and additive nois…
Accurate Deep Representation Quantization with Gradient Snapping Layer for Similarity Search
Shicong Liu, Hongtao Lu
Recent advance of large scale similarity search involves using deeply learned representations to improve the search accuracy and use vector quantization methods to increase the sea…
Multi-View Constraint Propagation with Consensus Prior Knowledge
Yaoyi Li, Hongtao Lu
In many applications, the pairwise constraint is a kind of weaker supervisory information which can be collected easily. The constraint propagation has been proved to be a success…
Deep CTR Prediction in Display Advertising
Junxuan Chen, Baigui Sun, Hao Li +2
Click through rate (CTR) prediction of image ads is the core task of online display advertising systems, and logistic regression (LR) has been frequently applied as the prediction…