activity
20182023
most citedSketch-Guided Scenery Image Outpainting

28 citations · 128 across the 19 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

cs.IR2021★ 3 cited

Multi-Sample based Contrastive Loss for Top-k Recommendation

Hao Tang, Guoshuai Zhao, Yuxia Wu +1

The top-k recommendation is a fundamental task in recommendation systems which is generally learned by comparing positive and negative pairs. The Contrastive Loss (CL) is the key i…

cs.CV2021

Generating Superpixels for High-resolution Images with Decoupled Patch Calibration

Yaxiong Wang, Yunchao Wei, Xueming Qian +2

Superpixel segmentation has recently seen important progress benefiting from the advances in differentiable deep learning. However, the very high-resolution superpixel segmentation…

cs.CV2021★ 3 cited

ReGO: Reference-Guided Outpainting for Scenery Image

Yaxiong Wang, Yunchao Wei, Xueming Qian +2

We aim to tackle the challenging yet practical scenery image outpainting task in this work. Recently, generative adversarial learning has significantly advanced the image outpainti…

cs.IR2021★ 1 cited

Diversity Regularized Interests Modeling for Recommender Systems

Junmei Hao, Jingcheng Shi, Qing Da +4

With the rapid development of E-commerce and the increase in the quantity of items, users are presented with more items hence their interests broaden. It is increasingly difficult…

cs.CV2021

AINet+: Advancing Superpixel Segmentation via Cascaded Association Implantation

Yaxiong Wang, Yunchao Wei, Yujiao Wu +3

Superpixel segmentation has seen significant progress benefiting from the deep convolutional networks. The typical approach entails initial division of the image into grids, follow…