584 citations · 698 across the 11 of their papers we have counts for
11 papers
Lightweight Human Pose Estimation Using Heatmap-Weighting Loss
Shiqi Li, Xiang Xiang
Recent research on human pose estimation exploits complex structures to improve performance on benchmark datasets, ignoring the resource overhead and inference speed when the model…
Hierarchical Memory Learning for Fine-Grained Scene Graph Generation
Youming Deng, Yansheng Li, Yongjun Zhang +4
As far as Scene Graph Generation (SGG), coarse and fine predicates mix in the dataset due to the crowd-sourced labeling, and the long-tail problem is also pronounced. Given this tr…
Long-Tailed Classification with Gradual Balanced Loss and Adaptive Feature Generation
Zihan Zhang, Xiang Xiang
The real-world data distribution is essentially long-tailed, which poses great challenge to the deep model. In this work, we propose a new method, Gradual Balanced Loss and Adaptiv…
Coarse-To-Fine Incremental Few-Shot Learning
Xiang Xiang, Yuwen Tan, Qian Wan +1
Different from fine-tuning models pre-trained on a large-scale dataset of preset classes, class-incremental learning (CIL) aims to recognize novel classes over time without forgett…
Adversarial Deep Structured Nets for Mass Segmentation from Mammograms
Wentao Zhu, Xiang Xiang, Trac D. Tran +2
Mass segmentation provides effective morphological features which are important for mass diagnosis. In this work, we propose a novel end-to-end network for mammographic mass segmen…
NormFace: L2 Hypersphere Embedding for Face Verification
Feng Wang, Xiang Xiang, Jian Cheng +1
Thanks to the recent developments of Convolutional Neural Networks, the performance of face verification methods has increased rapidly. In a typical face verification method, featu…
Regularizing Face Verification Nets For Pain Intensity Regression
Feng Wang, Xiang Xiang, Chang Liu +6
Limited labeled data are available for the research of estimating facial expression intensities. For instance, the ability to train deep networks for automated pain assessment is l…
Linear Disentangled Representation Learning for Facial Actions
Xiang Xiang, Trac D. Tran
Limited annotated data available for the recognition of facial expression and action units embarrasses the training of deep networks, which can learn disentangled invariant feature…
Adversarial Deep Structural Networks for Mammographic Mass Segmentation
Wentao Zhu, Xiang Xiang, Trac D. Tran +1
Mass segmentation is an important task in mammogram analysis, providing effective morphological features and regions of interest (ROI) for mass detection and classification. Inspir…
Pose-Selective Max Pooling for Measuring Similarity
Xiang Xiang, Trac D. Tran
In this paper, we deal with two challenges for measuring the similarity of the subject identities in practical video-based face recognition - the variation of the head pose in unco…
Hierarchical Sparse and Collaborative Low-Rank Representation for Emotion Recognition
Xiang Xiang, Minh Dao, Gregory D. Hager +1
In this paper, we design a Collaborative-Hierarchical Sparse and Low-Rank (C-HiSLR) model that is natural for recognizing human emotion in visual data. Previous attempts require ex…