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Dual Attention Network for Scene Segmentation
TLDR
New state-of-the-art segmentation performance on three challenging scene segmentation datasets, i.e., Cityscapes, PASCAL Context and COCO Stuff dataset is achieved without using coarse data. Expand
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition
TLDR
A novel two-stream adaptive graph convolutional network (2s-AGCN) for skeleton-based action recognition that increases the flexibility of the model for graph construction and brings more generality to adapt to various data samples. Expand
Unsupervised Feature Selection Using Nonnegative Spectral Analysis
TLDR
A new unsupervised learning algorithm, namely Nonnegative Discriminative Feature Selection (NDFS), which exploits the discriminative information and feature correlation simultaneously to select a better feature subset. Expand
A nonlinear approach for face sketch synthesis and recognition
TLDR
This paper presents a face recognition system based on face sketches that is based on pseudo-sketch synthesis and sketch recognition, and experimental results show that the performance of the proposed method is encouraging. Expand
Skeleton-Based Action Recognition With Directed Graph Neural Networks
TLDR
A novel directed graph neural network is designed specially to extract the information of joints, bones and their relations and make prediction based on the extracted features and is tested on two large-scale datasets, NTU-RGBD and Skeleton-Kinetics, and exceeds state-of-the-art performance on both of them. Expand
CoupleNet: Coupling Global Structure with Local Parts for Object Detection
TLDR
This paper proposes a novel fully convolutional network, named as CoupleNet, to couple the global structure with local parts for object detection and achieves state-of-the-art results on all three challenging datasets. Expand
Solving the small sample size problem of LDA
TLDR
This paper proposes a new method making use of the null space of S/sub w/ effectively and solve the small sample size problem of LDA, and compares its method with several well-known methods. Expand
Face detection using improved LBP under Bayesian framework
TLDR
A novel face detection approach using improved local binary patterns (ILBP) as facial representation that considers both local shape and texture information instead of raw grayscale information and it is robust to illumination variation. Expand
Online sketching hashing
TLDR
A novel approach to handle these two problems simultaneously based on the idea of data sketching, which can learn hash functions in an online fashion, while needs rather low computational complexity and storage space. Expand
Hi, magic closet, tell me what to wear!
TLDR
This paper collects a large clothing What-to-Wear dataset, and thoroughly annotates the whole dataset with 7 multi-value clothing attributes and 10 occasion categories via Amazon Mechanic Turk, to learn a generalize-well model and comprehensively evaluate it. Expand
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