157 citations · 1.3k across the 97 of their papers we have counts for
7 papers · 1 filter
Learning to Assemble Neural Module Tree Networks for Visual Grounding
Daqing Liu, Hanwang Zhang, Feng Wu +1
Visual grounding, a task to ground (i.e., localize) natural language in images, essentially requires composite visual reasoning. However, existing methods over-simplify the composi…
CA3Net: Contextual-Attentional Attribute-Appearance Network for Person Re-Identification
Jiawei Liu, Zheng-Jun Zha, Hongtao Xie +2
Person re-identification aims to identify the same pedestrian across non-overlapping camera views. Deep learning techniques have been applied for person re-identification recently,…
Context-Aware Visual Policy Network for Sequence-Level Image Captioning
Daqing Liu, Zheng-Jun Zha, Hanwang Zhang +2
Many vision-language tasks can be reduced to the problem of sequence prediction for natural language output. In particular, recent advances in image captioning use deep reinforceme…
A Two-Stream Mutual Attention Network for Semi-supervised Biomedical Segmentation with Noisy Labels
Shaobo Min, Xuejin Chen, Zheng-Jun Zha +2
\begin{abstract} Learning-based methods suffer from a deficiency of clean annotations, especially in biomedical segmentation. Although many semi-supervised methods have been propos…
Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System
Hong Wen, Jing Zhang, Quan Lin +2
Developing effective and efficient recommendation methods is very challenging for modern e-commerce platforms. Generally speaking, two essential modules named "Click-Through Rate P…
Frank-Wolfe Network: An Interpretable Deep Structure for Non-Sparse Coding
Dong Liu, Ke Sun, Zhangyang Wang +2
The problem of -norm constrained coding is to convert signal into code that lies inside an -ball and most faithfully reconstructs the signal. Previous works under the nam…
Fully Point-wise Convolutional Neural Network for Modeling Statistical Regularities in Natural Images
Jing Zhang, Yang Cao, Yang Wang +2
Modeling statistical regularity plays an essential role in ill-posed image processing problems. Recently, deep learning based methods have been presented to implicitly learn statis…