315 citations · 2.4k across the 76 of their papers we have counts for
21 papers · 1 filter
Multimodal In-bed Pose and Shape Estimation under the Blankets
Yu Yin, Joseph P. Robinson, Yun Fu
Humans spend vast hours in bed -- about one-third of the lifetime on average. Besides, a human at rest is vital in many healthcare applications. Typically, humans are covered by a…
SuperFront: From Low-resolution to High-resolution Frontal Face Synthesis
Yu Yin, Joseph P. Robinson, Songyao Jiang +3
Advances in face rotation, along with other face-based generative tasks, are more frequent as we advance further in topics of deep learning. Even as impressive milestones are achie…
Multi-head Knowledge Distillation for Model Compression
Huan Wang, Suhas Lohit, Michael Jones +1
Several methods of knowledge distillation have been developed for neural network compression. While they all use the KL divergence loss to align the soft outputs of the student mod…
Neural Pruning via Growing Regularization
Huan Wang, Can Qin, Yulun Zhang +1
Regularization has long been utilized to learn sparsity in deep neural network pruning. However, its role is mainly explored in the small penalty strength regime. In this work, we…
Collaborative Attention Mechanism for Multi-View Action Recognition
Yue Bai, Zhiqiang Tao, Lichen Wang +3
Multi-view action recognition (MVAR) leverages complementary temporal information from different views to improve the learning performance. Obtaining informative view-specific repr…
Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detection
Shuhan Chen, Yun Fu
In this paper, we aim to develop an efficient and compact deep network for RGB-D salient object detection, where the depth image provides complementary information to boost perform…
Families In Wild Multimedia: A Multimodal Database for Recognizing Kinship
Joseph P. Robinson, Zaid Khan, Yu Yin +2
Kinship, a soft biometric detectable in media, is fundamental for a myriad of use-cases. Despite the difficulty of detecting kinship, annual data challenges using still-images have…
Towards 3D Dance Motion Synthesis and Control
Wenlin Zhuang, Yangang Wang, Joseph Robinson +4
3D human dance motion is a cooperative and elegant social movement. Unlike regular simple locomotion, it is challenging to synthesize artistic dance motions due to the irregularity…
Neural Sparse Representation for Image Restoration
Yuchen Fan, Jiahui Yu, Yiqun Mei +4
Inspired by the robustness and efficiency of sparse representation in sparse coding based image restoration models, we investigate the sparsity of neurons in deep networks. Our met…
Survey on the Analysis and Modeling of Visual Kinship: A Decade in the Making
Joseph P Robinson, Ming Shao, Yun Fu
Kinship recognition is a challenging problem with many practical applications. With much progress and milestones having been reached after ten years - we are now able to survey the…
HyperSTAR: Task-Aware Hyperparameters for Deep Networks
Gaurav Mittal, Chang Liu, Nikolaos Karianakis +3
While deep neural networks excel in solving visual recognition tasks, they require significant effort to find hyperparameters that make them work optimally. Hyperparameter Optimiza…
Learnable Subspace Clustering
Jun Li, Hongfu Liu, Zhiqiang Tao +2
This paper studies the large-scale subspace clustering (LSSC) problem with million data points. Many popular subspace clustering methods cannot directly handle the LSSC problem alt…
Pyramid Attention Networks for Image Restoration
Yiqun Mei, Yuchen Fan, Yulun Zhang +6
Self-similarity refers to the image prior widely used in image restoration algorithms that small but similar patterns tend to occur at different locations and scales. However, rece…
Cross-Domain Document Object Detection: Benchmark Suite and Method
Kai Li, Curtis Wigington, Chris Tensmeyer +6
Decomposing images of document pages into high-level semantic regions (e.g., figures, tables, paragraphs), document object detection (DOD) is fundamental for downstream tasks like…
Generative Partial Multi-View Clustering
Qianqian Wang, Zhengming Ding, Zhiqiang Tao +2
Nowadays, with the rapid development of data collection sources and feature extraction methods, multi-view data are getting easy to obtain and have received increasing research att…
Adversarial Feature Hallucination Networks for Few-Shot Learning
Kai Li, Yulun Zhang, Kunpeng Li +1
The recent flourish of deep learning in various tasks is largely accredited to the rich and accessible labeled data. Nonetheless, massive supervision remains a luxury for many real…
Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution
Xiaoyu Xiang, Yapeng Tian, Yulun Zhang +3
In this paper, we explore the space-time video super-resolution task, which aims to generate a high-resolution (HR) slow-motion video from a low frame rate (LFR), low-resolution (L…
Dual-Attention GAN for Large-Pose Face Frontalization
Yu Yin, Songyao Jiang, Joseph P. Robinson +1
Face frontalization provides an effective and efficient way for face data augmentation and further improves the face recognition performance in extreme pose scenario. Despite recen…
Face Recognition: Too Bias, or Not Too Bias?
Joseph P Robinson, Gennady Livitz, Yann Henon +3
We reveal critical insights into problems of bias in state-of-the-art facial recognition (FR) systems using a novel Balanced Faces In the Wild (BFW) dataset: data balanced for gend…
Recognizing Families In the Wild: White Paper for the 4th Edition Data Challenge
Joseph P. Robinson, Yu Yin, Zaid Khan +7
Recognizing Families In the Wild (RFIW): an annual large-scale, multi-track automatic kinship recognition evaluation that supports various visual kin-based problems on scales much…
Contradictory Structure Learning for Semi-supervised Domain Adaptation
Can Qin, Lichen Wang, Qianqian Ma +3
Current adversarial adaptation methods attempt to align the cross-domain features, whereas two challenges remain unsolved: 1) the conditional distribution mismatch and 2) the bias…