1.1k citations · 1.2k across the 27 of their papers we have counts for
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Masked Momentum Contrastive Learning for Zero-shot Semantic Understanding
Jiantao Wu, Shentong Mo, Muhammad Awais +3
Self-supervised pretraining (SSP) has emerged as a popular technique in machine learning, enabling the extraction of meaningful feature representations without labelled data. In th…
FusionBooster: A Unified Image Fusion Boosting Paradigm
Chunyang Cheng, Tianyang Xu, Xiao-Jun Wu +3
In recent years, numerous ideas have emerged for designing a mutually reinforcing mechanism or extra stages for the image fusion task, ignoring the inevitable gaps between differen…
LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images
Hui Li, Tianyang Xu, Xiao-Jun Wu +2
Deep learning based fusion methods have been achieving promising performance in image fusion tasks. This is attributed to the network architecture that plays a very important role…
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…