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37,018 results
  • Few-Shot Deep Adversarial Learning for Video-based Person Re-identification. [Journal Article]
    IEEE Trans Image Process 2019Wu L, Wang Y, … Shao L
  • Video-based person re-identification (re-ID) refers to matching people across camera views from arbitrary unaligned video footages. Existing methods rely on supervision signals to optimise a projected space under which the distances between inter/intra-videos are maximised/minimised. However, this demands exhaustively labelling people across camera views, rendering them unable to be scaled in lar…
  • Deep Heterogeneous Hashing for Face Video Retrieval. [Journal Article]
    IEEE Trans Image Process 2019Qiao S, Wang R, … Chen X
  • Retrieving videos of a particular person with face image as query via hashing technique has many important applications. While face images are typically represented as vectors in Euclidean space, characterizing face videos with some robust set modeling techniques (e.g. covariance matrices as exploited in this study, which reside on Riemannian manifold), has recently shown appealing advantages. Th…
  • Learning Part-based Convolutional Features for Person Re-identification. [Journal Article]
    IEEE Trans Pattern Anal Mach Intell 2019Sun Y, Zheng L, … Wang S
  • Part-level features offers fine granularity for pedestrian image description. In this article, we generally aim to learn discriminative part-informed features for person re-identification. Our contribution is two-fold. First, we introduce a general part-level feature learning method, named Part-based Convolutional Baseline (PCB). Given an image, it outputs a convolutional descriptor consisting of…
  • Deep Differentiable Random Forests for Age Estimation. [Journal Article]
    IEEE Trans Pattern Anal Mach Intell 2019Shen W, Guo Y, … Yuille AL
  • Age estimation from facial images is typically cast as a label distribution learning or regression problem, since aging is a gradual progress. Its main challenge is the facial feature space w.r.t. ages is inhomogeneous, due to the large variation in facial appearance across different persons of the same age and the non-stationary property of aging. In this paper, we propose two Deep Differentiabl…
  • Adversarial Attack Type I: Cheat Classifiers by Significant Changes. [Journal Article]
    IEEE Trans Pattern Anal Mach Intell 2019Tang S, Huang X, … Yang J
  • Despite the great success of deep neural networks, the adversarial attack can cheat some well-trained classifiers by small permutations. In this paper, we propose another type of adversarial attack that can cheat classifiers by significant changes. For example, we can significantly change a face but well-trained neural networks still recognize the adversarial and the original example as the same …
  • Siamese Neural Networks for User Identity Linkage Through Web Browsing. [Journal Article]
    IEEE Trans Neural Netw Learn Syst 2019Qiao Y, Wu Y, … Yang J
  • Linking online identities of users among countless heterogeneous network services on the Internet can provide an explicit digital representation of users, which can benefit both research and industry. In recent years, user identity linkage (UIL) through the Internet has become an emerging task with great potential and many challenges. Existing works mainly focus on online social networks that con…
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