861 citations · 983 across the 9 of their papers we have counts for
5 papers · 1 filter
Attentional Local Contrast Networks for Infrared Small Target Detection
Yimian Dai, Yiquan Wu, Fei Zhou +1
To mitigate the issue of minimal intrinsic features for pure data-driven methods, in this paper, we propose a novel model-driven deep network for infrared small target detection, w…
Asymmetric Contextual Modulation for Infrared Small Target Detection
Yimian Dai, Yiquan Wu, Fei Zhou +1
Single-frame infrared small target detection remains a challenge not only due to the scarcity of intrinsic target characteristics but also because of lacking a public dataset. In t…
Attentional Feature Fusion
Yimian Dai, Fabian Gieseke, Stefan Oehmcke +2
Feature fusion, the combination of features from different layers or branches, is an omnipresent part of modern network architectures. It is often implemented via simple operations…
Attention as Activation
Yimian Dai, Stefan Oehmcke, Fabian Gieseke +2
Activation functions and attention mechanisms are typically treated as having different purposes and have evolved differently. However, both concepts can be formulated as a non-lin…
Branching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D Trees
Kyle Simek, Ravishankar Palanivelu, Kobus Barnard
We propose a robust method for estimating dynamic 3D curvilinear branching structure from monocular images. While 3D reconstruction from images has been widely studied, estimating…