3.6k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN16 papers
- Mohamed bin Zayed University of Artificial IntelligenceAE16 papers
- Nankai UniversityCN16 papers
- ETH ZurichCH12 papers
- Tianjin UniversityCN12 papers
- University of Electronic Science and Technology of ChinaCN11 papers
- Southern University of Science and TechnologyCN9 papers
- University of AmsterdamNL9 papers
- Beijing Institute of TechnologyCN8 papers
- Wuhan UniversityCN8 papers
- Australian National UniversityAU7 papers
- Harbin Institute of TechnologyCN7 papers
19 papers · 1 filter
3D PersonVLAD: Learning Deep Global Representations for Video-based Person Re-identification
Lin Wu, Yang Wang, Ling Shao +1
In this paper, we introduce a global video representation to video-based person re-identification (re-ID) that aggregates local 3D features across the entire video extent. Most of…
A Survey on Deep Learning for Named Entity Recognition
Jing Li, Aixin Sun, Jianglei Han +1
Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types such as person, location, organization etc. NE…
HSCS: Hierarchical Sparsity Based Co-saliency Detection for RGBD Images
Runmin Cong, Jianjun Lei, Huazhu Fu +3
Co-saliency detection aims to discover common and salient objects in an image group containing more than two relevant images. Moreover, depth information has been demonstrated to b…
Submodular Optimization Over Streams with Inhomogeneous Decays
Junzhou Zhao, Shuo Shang, Pinghui Wang +2
Cardinality constrained submodular function maximization, which aims to select a subset of size at most to maximize a monotone submodular utility function, is the key in many d…
Variational Bayesian Dropout with a Hierarchical Prior
Yuhang Liu, Wenyong Dong, Lei Zhang +2
Variational dropout (VD) is a generalization of Gaussian dropout, which aims at inferring the posterior of network weights based on a log-uniform prior on them to learn these weigh…
Confidence Propagation through CNNs for Guided Sparse Depth Regression
Abdelrahman Eldesokey, Michael Felsberg, Fahad Shahbaz Khan
Generally, convolutional neural networks (CNNs) process data on a regular grid, e.g. data generated by ordinary cameras. Designing CNNs for sparse and irregularly spaced input data…
Tracking Influential Nodes in Time-Decaying Dynamic Interaction Networks
Junzhou Zhao, Shuo Shang, Pinghui Wang +2
Identifying influential nodes that can jointly trigger the maximum influence spread in networks is a fundamental problem in many applications such as viral marketing, online advert…
Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition
Jian Zhao, Yu Cheng, Yi Cheng +12
Despite the remarkable progress in face recognition related technologies, reliably recognizing faces across ages still remains a big challenge. The appearance of a human face chang…
Highly-Economized Multi-View Binary Compression for Scalable Image Clustering
Zheng Zhang, Li Liu, Jie Qin +5
How to economically cluster large-scale multi-view images is a long-standing problem in computer vision. To tackle this challenge, we introduce a novel approach named Highly-econom…
Improving the results of string kernels in sentiment analysis and Arabic dialect identification by adapting them to your test set
Radu Tudor Ionescu, Andrei M. Butnaru
Recently, string kernels have obtained state-of-the-art results in various text classification tasks such as Arabic dialect identification or native language identification. In thi…
Learning Human-Object Interactions by Graph Parsing Neural Networks
Siyuan Qi, Wenguan Wang, Baoxiong Jia +2
This paper addresses the task of detecting and recognizing human-object interactions (HOI) in images and videos. We introduce the Graph Parsing Neural Network (GPNN), a framework t…
Visual Affordance and Function Understanding: A Survey
Mohammed Hassanin, Salman Khan, Murat Tahtali
Nowadays, robots are dominating the manufacturing, entertainment and healthcare industries. Robot vision aims to equip robots with the ability to discover information, understand i…
Scaled Simplex Representation for Subspace Clustering
Jun Xu, Mengyang Yu, Ling Shao +4
The self-expressive property of data points, i.e., each data point can be linearly represented by the other data points in the same subspace, has proven effective in leading subspa…
Synthetic data generation for end-to-end thermal infrared tracking
Lichao Zhang, Abel Gonzalez-Garcia, Joost van de Weijer +2
The usage of both off-the-shelf and end-to-end trained deep networks have significantly improved performance of visual tracking on RGB videos. However, the lack of large labeled da…
Optimizing the F-measure for Threshold-free Salient Object Detection
Kai Zhao, Shanghua Gao, Wenguan Wang +1
Current CNN-based solutions to salient object detection (SOD) mainly rely on the optimization of cross-entropy loss (CELoss). Then the quality of detected saliency maps is often ev…
Cycle-Consistent Deep Generative Hashing for Cross-Modal Retrieval
Lin Wu, Yang Wang, Ling Shao
In this paper, we propose a novel deep generative approach to cross-modal retrieval to learn hash functions in the absence of paired training samples through the cycle consistency…
Towards Universal Representation for Unseen Action Recognition
Yi Zhu, Yang Long, Yu Guan +2
Unseen Action Recognition (UAR) aims to recognise novel action categories without training examples. While previous methods focus on inner-dataset seen/unseen splits, this paper pr…
Zero-Shot Sketch-Image Hashing
Yuming Shen, Li Liu, Fumin Shen +1
Recent studies show that large-scale sketch-based image retrieval (SBIR) can be efficiently tackled by cross-modal binary representation learning methods, where Hamming distance ma…
Review of Visual Saliency Detection with Comprehensive Information
Runmin Cong, Jianjun Lei, Huazhu Fu +3
Visual saliency detection model simulates the human visual system to perceive the scene, and has been widely used in many vision tasks. With the acquisition technology development,…