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ASiT: Local-Global Audio Spectrogram vIsion Transformer for Event Classification
Sara Atito, Muhammad Awais, Wenwu Wang +2
Transformers, which were originally developed for natural language processing, have recently generated significant interest in the computer vision and audio communities due to thei…
RGBD1K: A Large-scale Dataset and Benchmark for RGB-D Object Tracking
Xue-Feng Zhu, Tianyang Xu, Zhangyong Tang +5
RGB-D object tracking has attracted considerable attention recently, achieving promising performance thanks to the symbiosis between visual and depth channels. However, given a lim…
DreamNet: A Deep Riemannian Network based on SPD Manifold Learning for Visual Classification
Rui Wang, Xiao-Jun Wu, Ziheng Chen +2
Image set-based visual classification methods have achieved remarkable performance, via characterising the image set in terms of a non-singular covariance matrix on a symmetric pos…
GMML is All you Need
Sara Atito, Muhammad Awais, Josef Kittler
Vision transformers have generated significant interest in the computer vision community because of their flexibility in exploiting contextual information, whether it is sharply co…
Importance Weighted Structure Learning for Scene Graph Generation
Daqi Liu, Miroslaw Bober, Josef Kittler
Scene graph generation is a structured prediction task aiming to explicitly model objects and their relationships via constructing a visually-grounded scene graph for an input imag…
Constrained Structure Learning for Scene Graph Generation
Daqi Liu, Miroslaw Bober, Josef Kittler
As a structured prediction task, scene graph generation aims to build a visually-grounded scene graph to explicitly model objects and their relationships in an input image. Current…
Exploring Fusion Strategies for Accurate RGBT Visual Object Tracking
Zhangyong Tang, Tianyang Xu, Hui Li +3
We address the problem of multi-modal object tracking in video and explore various options of fusing the complementary information conveyed by the visible (RGB) and thermal infrare…
Riemannian Local Mechanism for SPD Neural Networks
Ziheng Chen, Tianyang Xu, Xiao-Jun Wu +3
The Symmetric Positive Definite (SPD) matrices have received wide attention for data representation in many scientific areas. Although there are many different attempts to develop…