150 citations · 211 across the 7 of their papers we have counts for
7 papers
FUSE: Multi-Faceted Set Expansion by Coherent Clustering of Skip-grams
Wanzheng Zhu, Hongyu Gong, Jiaming Shen +4
Set expansion aims to expand a small set of seed entities into a complete set of relevant entities. Most existing approaches assume the input seed set is unambiguous and completely…
Interlaced Sparse Self-Attention for Semantic Segmentation
Lang Huang, Yuhui Yuan, Jianyuan Guo +3
In this paper, we present a so-called interlaced sparse self-attention approach to improve the efficiency of the \emph{self-attention} mechanism for semantic segmentation. The main…
Multi-scale Template Matching with Scalable Diversity Similarity in an Unconstrained Environment
Yi Zhang, Chao Zhang, Takuya Akashi
We propose a novel multi-scale template matching method which is robust against both scaling and rotation in unconstrained environments. The key component behind is a similarity me…
A Probabilistic Bitwise Genetic Algorithm for B-Spline based Image Deformation Estimation
Takumi Nakane, Takuya Akashi, Xuequan Lu +1
We propose a novel genetic algorithm to solve the image deformation estimation problem by preserving the genetic diversity. As a classical problem, there is always a trade-off betw…
Attribute-Aware Attention Model for Fine-grained Representation Learning
Kai Han, Jianyuan Guo, Chao Zhang +1
How to learn a discriminative fine-grained representation is a key point in many computer vision applications, such as person re-identification, fine-grained classification, fine-g…
Cross-domain Deep Feature Combination for Bird Species Classification with Audio-visual Data
Bold Naranchimeg, Chao Zhang, Takuya Akashi
In recent decade, many state-of-the-art algorithms on image classification as well as audio classification have achieved noticeable successes with the development of deep convoluti…
Robust Spatial Filtering with Graph Convolutional Neural Networks
Felipe Petroski Such, Shagan Sah, Miguel Dominguez +5
Convolutional Neural Networks (CNNs) have recently led to incredible breakthroughs on a variety of pattern recognition problems. Banks of finite impulse response filters are learne…