5 citations · 6 across the 4 of their papers we have counts for
6 papers
End-to-end video instance segmentation via spatial-temporal graph neural networks
Tao Wang, Ning Xu, Kean Chen +1
Video instance segmentation is a challenging task that extends image instance segmentation to the video domain. Existing methods either rely only on single-frame information for th…
Instance-Dependent Partial Label Learning
Ning Xu, Congyu Qiao, Xin Geng +1
Partial label learning (PLL) is a typical weakly supervised learning problem, where each training example is associated with a set of candidate labels among which only one is true.…
Delving into the Cyclic Mechanism in Semi-supervised Video Object Segmentation
Yuxi Li, Ning Xu, Jinlong Peng +2
In this paper, we address several inadequacies of current video object segmentation pipelines. Firstly, a cyclic mechanism is incorporated to the standard semi-supervised process t…
A Benchmark and Baseline for Language-Driven Image Editing
Jing Shi, Ning Xu, Trung Bui +3
Language-driven image editing can significantly save the laborious image editing work and be friendly to the photography novice. However, most similar work can only deal with a spe…
Compact Learning for Multi-Label Classification
Jiaqi Lv, Tianran Wu, Chenglun Peng +3
Multi-label classification (MLC) studies the problem where each instance is associated with multiple relevant labels, which leads to the exponential growth of output space. MLC enc…
High-Resolution Deep Image Matting
Haichao Yu, Ning Xu, Zilong Huang +2
Image matting is a key technique for image and video editing and composition. Conventionally, deep learning approaches take the whole input image and an associated trimap to infer…