315 citations · 2.4k across the 76 of their papers we have counts for
20 papers · 1 filter
Texture Hallucination for Large-Factor Painting Super-Resolution
Yulun Zhang, Zhifei Zhang, Stephen DiVerdi +3
We aim to super-resolve digital paintings, synthesizing realistic details from high-resolution reference painting materials for very large scaling factors (e.g., 8X, 16X). However,…
Lifelong Spectral Clustering
Gan Sun, Yang Cong, Qianqian Wang +2
In the past decades, spectral clustering (SC) has become one of the most effective clustering algorithms. However, most previous studies focus on spectral clustering tasks with a f…
Joint Super-Resolution and Alignment of Tiny Faces
Yu Yin, Joseph P. Robinson, Yulun Zhang +1
Super-resolution (SR) and landmark localization of tiny faces are highly correlated tasks. On the one hand, landmark localization could obtain higher accuracy with faces of high-re…
What Will Your Child Look Like? DNA-Net: Age and Gender Aware Kin Face Synthesizer
Pengyu Gao, Siyu Xia, Joseph Robinson +4
Visual kinship recognition aims to identify blood relatives from facial images. Its practical application-- like in law-enforcement, video surveillance, automatic family album mana…
LPRNet: Lightweight Deep Network by Low-rank Pointwise Residual Convolution
Bin Sun, Jun Li, Ming Shao +1
Deep learning has become popular in recent years primarily due to the powerful computing device such as GPUs. However, deploying these deep models to end-user devices, smart phones…
PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation
Can Qin, Haoxuan You, Lichen Wang +2
Domain Adaptation (DA) approaches achieved significant improvements in a wide range of machine learning and computer vision tasks (i.e., classification, detection, and segmentation…
Correlative Channel-Aware Fusion for Multi-View Time Series Classification
Yue Bai, Lichen Wang, Zhiqiang Tao +2
Multi-view time series classification (MVTSC) aims to improve the performance by fusing the distinctive temporal information from multiple views. Existing methods mainly focus on f…
Real-time Memory Efficient Large-pose Face Alignment via Deep Evolutionary Network
Bin Sun, Ming Shao, Siyu Xia +1
There is an urgent need to apply face alignment in a memory-efficient and real-time manner due to the recent explosion of face recognition applications. However, impact factors suc…
Generative One-Shot Face Recognition
Zhengming Ding, Yandong Guo, Lei Zhang +1
One-shot face recognition measures the ability to identify persons with only seeing them at one glance, and is a hallmark of human visual intelligence. It is challenging for conven…
Visual Semantic Reasoning for Image-Text Matching
Kunpeng Li, Yulun Zhang, Kai Li +2
Image-text matching has been a hot research topic bridging the vision and language areas. It remains challenging because the current representation of image usually lacks global se…
Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective
Kai Li, Martin Renqiang Min, Yun Fu
Zero-shot learning (ZSL) aims to recognize instances of unseen classes solely based on the semantic descriptions of the classes. Existing algorithms usually formulate it as a seman…
Large Scale Incremental Learning
Yue Wu, Yinpeng Chen, Lijuan Wang +4
Modern machine learning suffers from catastrophic forgetting when learning new classes incrementally. The performance dramatically degrades due to the missing data of old classes.…
Spatially Constrained GAN for Face and Fashion Synthesis
Songyao Jiang, Hongfu Liu, Yue Wu +1
Image generation has raised tremendous attention in both academic and industrial areas, especially for the conditional and target-oriented image generation, such as criminal portra…
EV-Action: Electromyography-Vision Multi-Modal Action Dataset
Lichen Wang, Bin Sun, Joseph Robinson +2
Multi-modal human action analysis is a critical and attractive research topic. However, the majority of the existing datasets only provide visual modalities (i.e., RGB, depth and s…
Rethinking Classification and Localization for Object Detection
Yue Wu, Yinpeng Chen, Lu Yuan +4
Two head structures (i.e. fully connected head and convolution head) have been widely used in R-CNN based detectors for classification and localization tasks. However, there is a l…
Multimodal Style Transfer via Graph Cuts
Yulun Zhang, Chen Fang, Yilin Wang +4
An assumption widely used in recent neural style transfer methods is that image styles can be described by global statics of deep features like Gram or covariance matrices. Alterna…
Residual Non-local Attention Networks for Image Restoration
Yulun Zhang, Kunpeng Li, Kai Li +2
In this paper, we propose a residual non-local attention network for high-quality image restoration. Without considering the uneven distribution of information in the corrupted ima…
Laplace Landmark Localization
Joseph P Robinson, Yuncheng Li, Ning Zhang +2
Landmark localization in images and videos is a classic problem solved in various ways. Nowadays, with deep networks prevailing throughout machine learning, there are revamped inte…
Representative Task Self-selection for Flexible Clustered Lifelong Learning
Gan Sun, Yang Cong, Qianqian Wang +2
Consider the lifelong machine learning paradigm whose objective is to learn a sequence of tasks depending on previous experiences, e.g., knowledge library or deep network weights.…
Segmentation Guided Image-to-Image Translation with Adversarial Networks
Songyao Jiang, Zhiqiang Tao, Yun Fu
Recently image-to-image translation has received increasing attention, which aims to map images in one domain to another specific one. Existing methods mainly solve this task via a…