Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN2.9k papers
- Centre National de la Recherche ScientifiqueFR2.7k papers
- Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di FrascatiIT2.6k papers
- Institute of High Energy PhysicsCN2.6k papers
- University of Science and Technology of ChinaCN2.5k papers
- Peking UniversityCN2.4k papers
- University of Chinese Academy of SciencesCN2.3k papers
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma IIT2.3k papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR2.3k papers
- Rutherford Appleton LaboratoryGB2.2k papers
- Istituto Nazionale di Fisica Nucleare, Sezione di GenovaIT2.2k papers
- European Organization for Nuclear ResearchCH2.2k papers
27 papers · 2 filters
Two-stream convolutional neural network for accurate RGB-D fingertip detection using depth and edge information
Hengkai Guo, Guijin Wang, Xinghao Chen
Accurate detection of fingertips in depth image is critical for human-computer interaction. In this paper, we present a novel two-stream convolutional neural network (CNN) for RGB-…
UnrealStereo: Controlling Hazardous Factors to Analyze Stereo Vision
Yi Zhang, Weichao Qiu, Qi Chen +2
A reliable stereo algorithm is critical for many robotics applications. But textureless and specular regions can easily cause failure by making feature matching difficult. Understa…
Person Re-Identification by Unsupervised Video Matching
Xiaolong Ma, Xiatian Zhu, Shaogang Gong +4
Most existing person re-identification (ReID) methods rely only on the spatial appearance information from either one or multiple person images, whilst ignore the space-time cues r…
Max-Margin Deep Generative Models for (Semi-)Supervised Learning
Chongxuan Li, Jun Zhu, Bo Zhang
Deep generative models (DGMs) are effective on learning multilayered representations of complex data and performing inference of input data by exploring the generative ability. How…
End-to-End Subtitle Detection and Recognition for Videos in East Asian Languages via CNN Ensemble with Near-Human-Level Performance
Yan Xu, Siyuan Shan, Ziming Qiu +5
In this paper, we propose an innovative end-to-end subtitle detection and recognition system for videos in East Asian languages. Our end-to-end system consists of multiple stages.…
Multi-View 3D Object Detection Network for Autonomous Driving
Xiaozhi Chen, Huimin Ma, Ji Wan +2
This paper aims at high-accuracy 3D object detection in autonomous driving scenario. We propose Multi-View 3D networks (MV3D), a sensory-fusion framework that takes both LIDAR poin…
Fully Convolutional Instance-aware Semantic Segmentation
Yi Li, Haozhi Qi, Jifeng Dai +2
We present the first fully convolutional end-to-end solution for instance-aware semantic segmentation task. It inherits all the merits of FCNs for semantic segmentation and instanc…
Associative Embedding: End-to-End Learning for Joint Detection and Grouping
Alejandro Newell, Zhiao Huang, Jia Deng
We introduce associative embedding, a novel method for supervising convolutional neural networks for the task of detection and grouping. A number of computer vision problems can be…
Image-embodied Knowledge Representation Learning
Ruobing Xie, Zhiyuan Liu, Huanbo Luan +1
Entity images could provide significant visual information for knowledge representation learning. Most conventional methods learn knowledge representations merely from structured t…
A Systematic Approach for Cross-source Point Cloud Registration by Preserving Macro and Micro Structures
Xiaoshui Huang, Jian Zhang, Lixin Fan +2
We propose a systematic approach for registering cross-source point clouds. The compelling need for cross-source point cloud registration is motivated by the rapid development of a…
Edge Preserving and Multi-Scale Contextual Neural Network for Salient Object Detection
Xiang Wang, Huimin Ma, Xiaozhi Chen +1
In this paper, we propose a novel edge preserving and multi-scale contextual neural network for salient object detection. The proposed framework is aiming to address two limits of…
Densely Connected Convolutional Networks
Gao Huang, Zhuang Liu, Laurens van der Maaten +1
Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the…
High-speed real-time single-pixel microscopy based on Fourier sampling
Qiang Guo, Hongwei Chen, Yuxi Wang +8
Single-pixel cameras based on the concepts of compressed sensing (CS) leverage the inherent structure of images to retrieve them with far fewer measurements and operate efficiently…
Towards Better Analysis of Deep Convolutional Neural Networks
Mengchen Liu, Jiaxin Shi, Zhen Li +3
Deep convolutional neural networks (CNNs) have achieved breakthrough performance in many pattern recognition tasks such as image classification. However, the development of high-qu…
Learning Attributes Equals Multi-Source Domain Generalization
Chuang Gan, Tianbao Yang, Boqing Gong
Attributes possess appealing properties and benefit many computer vision problems, such as object recognition, learning with humans in the loop, and image retrieval. Whereas the ex…
Engineering Deep Representations for Modeling Aesthetic Perception
Yanxiang Chen, Yuxing Hu, Luming Zhang +2
Many aesthetic models in computer vision suffer from two shortcomings: 1) the low descriptiveness and interpretability of those hand-crafted aesthetic criteria (i.e., nonindicative…
R-FCN: Object Detection via Region-based Fully Convolutional Networks
Jifeng Dai, Yi Li, Kaiming He +1
We present region-based, fully convolutional networks for accurate and efficient object detection. In contrast to previous region-based detectors such as Fast/Faster R-CNN that app…
Scalable low dimensional manifold model in the reconstruction of noisy and incomplete hyperspectral images
Wei Zhu, Zuoqiang Shi, Stanley Osher
We present a scalable low dimensional manifold model for the reconstruction of noisy and incomplete hyperspectral images. The model is based on the observation that the spatial-spe…
HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection
Tao Kong, Anbang Yao, Yurong Chen +1
Almost all of the current top-performing object detection networks employ region proposals to guide the search for object instances. State-of-the-art region proposal methods usuall…
Correlated and Individual Multi-Modal Deep Learning for RGB-D Object Recognition
Ziyan Wang, Jiwen Lu, Ruogu Lin +2
In this paper, we propose a new correlated and individual multi-modal deep learning (CIMDL) method for RGB-D object recognition. Unlike most conventional RGB-D object recognition m…
Instance-sensitive Fully Convolutional Networks
Jifeng Dai, Kaiming He, Yi Li +2
Fully convolutional networks (FCNs) have been proven very successful for semantic segmentation, but the FCN outputs are unaware of object instances. In this paper, we develop FCNs…
Appearance Harmonization for Single Image Shadow Removal
Liqian Ma, Jue Wang, Eli Shechtman +2
Shadows often create unwanted artifacts in photographs, and removing them can be very challenging. Previous shadow removal methods often produce de-shadowed regions that are visual…
Fourier ptychographic reconstruction using Poisson maximum likelihood and truncated Wirtinger gradient
Liheng Bian, Jinli Suo, Jaebum Chung +4
Fourier ptychographic microscopy (FPM) is a novel computational coherent imaging technique for high space-bandwidth product imaging. Mathematically, Fourier ptychographic (FP) reco…
Learning Domain-Invariant Subspace using Domain Features and Independence Maximization
Ke Yan, Lu Kou, David Zhang
Domain adaptation algorithms are useful when the distributions of the training and the test data are different. In this paper, we focus on the problem of instrumental variation and…