Abstract Unseen Action Recognition (UAR) aims to recognise novel action categories
without training examples. While previous methods focus on inner-dataset seen/unseen …

Mid-level or semi-local features learnt using class-level information are potentially more
distinctive than the traditional low-level local features constructed in a purely bottom-up …

Occlusion is one of the most intractable problems for face recognition. Double-occlusion
problem is an extremely challenging case that the occlusion can occur in both of training …

Abstract Since Convolutional Neural Networks (CNNs) have become the leading learning
paradigm in visual recognition, Naive Bayes Nearest Neighbor (NBNN)-based classifiers …

Local features have been widely used in computer vision tasks, eg, human action
recognition, but it tends to be an extremely challenging task to deal with large-scale local …

We propose a discriminative compact scene descriptor for single-view cross-season place
recognition. Unlike previous bag-of-words approaches which rely on a library of vector …

朴素贝叶斯最近邻(NBNN) 分类算法具有非特征量化和图像-类别度量方式的优点,
但算法运行速度较慢, 分类正确率较低. 针对此问题, 提出一种朴素贝叶斯K 近邻分类算法 …

Abstract Image-to-Class (I2C) distance firstly proposed in the naive Bayes nearest
neighbour (NBNN) classifier has shown its effectiveness in image classification. However …

This paper mainly focuses on how to effectively and efficiently measure visual similarity for
local feature based representation. Among existing methods, metrics based on Bag of Visual …

Long-term visual SLAM, in familiar, semi-dynamic, and partially changing environments is
an important area of research in robotics. The main problem we faced is the question of how …