Incremental Learning for Place Recognition in Dynamic Environments
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Despite the significant progress in recent years, deep face recognition is often treated as a "black box" and has been criticized for lacking explainability. It becomes increasingly important to understand the characteristics and decisions of deep face rec ...
A large body of research has focused on adversarial attacks which require to modify all input features with small l2- or l∞-norms. In this paper we instead focus on query-efficient sparse attacks in the black-box setting. Our versatile framework, Sparse-RS ...
Comic book digitization would play a pivotal role in exploring new avenues on how digital comics can be consumed. As of present, the systems capable of doing such a task are limited in capability to achieve complete digitization. This task of digitization ...
A large part of computer vision research is devoted to building models
and algorithms aimed at understanding human appearance and behaviour
from images and videos. Ultimately, we want to build automated systems
that are at least as capable as people when i ...
This paper investigates the automatic recognition of social roles that emerge naturally in small groups. These roles represent a flexible classification scheme that can generalize across different scenarios of small group interaction. We systematically inv ...
The architectural projects and building operations conducted over the past three decades by Patrick Bouchain and his collaborators challenge a series of assumptions regarding architecture’s authorship, its purpose and usage. Examined in light of Paul Ricoe ...
Hand gesture-to-gesture translation in the wild is a challenging task since hand gestures can have arbitrary poses, sizes, locations and self-occlusions. Therefore, this task requires a high-level understanding of the mapping between the input source gestu ...
This paper proposes a new method for recognizing both activities and gestures by using acceleration data collected on a smartwatch. While both activity recognition techniques and gesture recognition techniques employ acceleration data, these techniques are ...
HMMs have been the one of the first models to be applied for sign recognition and have become the baseline models due to their success in modeling sequential and multivariate data. Despite the extensive use of HMMs for sign recognition, determining the HMM ...
Crowdsourcing is a popular tool for conducting subjective evaluations in uncontrolled environments and at low cost. In this paper, a crowdsourcing study is conducted to investigate the impact of High Dynamic Range (HDR) imaging on subjective face recogniti ...
