539 citations · 715 across the 7 of their papers we have counts for
7 papers
MomentDiff: Generative Video Moment Retrieval from Random to Real
Pandeng Li, Chen-Wei Xie, Hongtao Xie +5
Video moment retrieval pursues an efficient and generalized solution to identify the specific temporal segments within an untrimmed video that correspond to a given language descri…
EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, Featuring Prognostic Stratification Boosting
Hassan Muhammad, Chensu Xie, Carlie S. Sigel +5
Histopathology-based survival modelling has two major hurdles. Firstly, a well-performing survival model has minimal clinical application if it does not contribute to the stratific…
Vortex Pooling: Improving Context Representation in Semantic Segmentation
Chen-Wei Xie, Hong-Yu Zhou, Jianxin Wu
Semantic segmentation is a fundamental task in computer vision, which can be considered as a per-pixel classification problem. Recently, although fully convolutional neural network…
Deep Descriptor Transforming for Image Co-Localization
Xiu-Shen Wei, Chen-Lin Zhang, Yao Li +4
Reusable model design becomes desirable with the rapid expansion of machine learning applications. In this paper, we focus on the reusability of pre-trained deep convolutional mode…
Deep Label Distribution Learning with Label Ambiguity
Bin-Bin Gao, Chao Xing, Chen-Wei Xie +2
Convolutional Neural Networks (ConvNets) have achieved excellent recognition performance in various visual recognition tasks. A large labeled training set is one of the most import…
Dense CNN Learning with Equivalent Mappings
Jianxin Wu, Chen-Wei Xie, Jian-Hao Luo
Large receptive field and dense prediction are both important for achieving high accuracy in pixel labeling tasks such as semantic segmentation. These two properties, however, cont…
Mask-CNN: Localizing Parts and Selecting Descriptors for Fine-Grained Image Recognition
Xiu-Shen Wei, Chen-Wei Xie, Jianxin Wu
Fine-grained image recognition is a challenging computer vision problem, due to the small inter-class variations caused by highly similar subordinate categories, and the large intr…