Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Mallis, Dimitrios"'
Autor:
Karadeniz, Ahmet Serdar, Mallis, Dimitrios, Mejri, Nesryne, Cherenkova, Kseniya, Kacem, Anis, Aouada, Djamila
We propose PICASSO, a novel framework CAD sketch parameterization from hand-drawn or precise sketch images via rendering self-supervision. Given a drawing of a CAD sketch, the proposed framework turns it into parametric primitives that can be importe
Externí odkaz:
http://arxiv.org/abs/2407.13394
Autor:
Dupont, Elona, Cherenkova, Kseniya, Mallis, Dimitrios, Gusev, Gleb, Kacem, Anis, Aouada, Djamila
3D reverse engineering, in which a CAD model is inferred given a 3D scan of a physical object, is a research direction that offers many promising practical applications. This paper proposes TransCAD, an end-to-end transformer-based architecture that
Externí odkaz:
http://arxiv.org/abs/2407.12702
Autor:
Anastasakis, Zacharias, Mallis, Dimitrios, Diomataris, Markos, Alexandridis, George, Kollias, Stefanos, Pitsikalis, Vassilis
We present a novel self-supervised approach for representation learning, particularly for the task of Visual Relationship Detection (VRD). Motivated by the effectiveness of Masked Image Modeling (MIM), we propose Masked Bounding Box Reconstruction (M
Externí odkaz:
http://arxiv.org/abs/2311.04834
Transformer-based architectures have recently demonstrated remarkable performance in the Visual Question Answering (VQA) task. However, such models are likely to disregard crucial visual cues and often rely on multimodal shortcuts and inherent biases
Externí odkaz:
http://arxiv.org/abs/2309.03726
Autor:
Mallis, Dimitrios, Ali, Sk Aziz, Dupont, Elona, Cherenkova, Kseniya, Karadeniz, Ahmet Serdar, Khan, Mohammad Sadil, Kacem, Anis, Gusev, Gleb, Aouada, Djamila
Recent breakthroughs in geometric Deep Learning (DL) and the availability of large Computer-Aided Design (CAD) datasets have advanced the research on learning CAD modeling processes and relating them to real objects. In this context, 3D reverse engin
Externí odkaz:
http://arxiv.org/abs/2308.15966
Autor:
Katsileros, Petros, Mandilaras, Nikiforos, Mallis, Dimitrios, Pitsikalis, Vassilis, Theodorakis, Stavros, Chamiel, Gil
In this work we introduce an incremental learning framework for Click-Through-Rate (CTR) prediction and demonstrate its effectiveness for Taboola's massive-scale recommendation service. Our approach enables rapid capture of emerging trends through wa
Externí odkaz:
http://arxiv.org/abs/2209.00458
This paper proposes a novel paradigm for the unsupervised learning of object landmark detectors. Contrary to existing methods that build on auxiliary tasks such as image generation or equivariance, we propose a self-training approach where, departing
Externí odkaz:
http://arxiv.org/abs/2205.15895
Publikováno v:
Evolving Systems, Volume 9, Issue 4, pp 315,329, December 2018
Audio source separation is the task of isolating sound sources that are active simultaneously in a room captured by a set of microphones. Convolutive audio source separation of equal number of sources and microphones has a number of shortcomings incl
Externí odkaz:
http://arxiv.org/abs/1708.03989
Publikováno v:
Journal of Systems and Information Technology, 2018, Vol. 20, Issue 2, pp. 130-151.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JSIT-06-2017-0040
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