51 citations · 111 across the 11 of their papers we have counts for
9 papers · 1 filter
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…
Efficient Hybrid Network: Inducting Scattering Features
Dmitry Minskiy, Miroslaw Bober
Recent work showed that hybrid networks, which combine predefined and learnt filters within a single architecture, are more amenable to theoretical analysis and less prone to overf…
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…
ACTNET: end-to-end learning of feature activations and multi-stream aggregation for effective instance image retrieval
Syed Sameed Husain, Eng-Jon Ong, Miroslaw Bober
We propose a novel CNN architecture called ACTNET for robust instance image retrieval from large-scale datasets. Our key innovation is a learnable activation layer designed to impr…
REMAP: Multi-layer entropy-guided pooling of dense CNN features for image retrieval
Syed Sameed Husain, Miroslaw Bober
This paper addresses the problem of very large-scale image retrieval, focusing on improving its accuracy and robustness. We target enhanced robustness of search to factors such as…
Visual Semantic Information Pursuit: A Survey
Daqi Liu, Miroslaw Bober, Josef Kittler
Visual semantic information comprises two important parts: the meaning of each visual semantic unit and the coherent visual semantic relation conveyed by these visual semantic unit…