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In this paper, we study salient object classification: a more realistic scenario where there are multiple object instances in the scene, and we are interested ...
In this paper, we study salient object classification: a more realistic scenario where there are multiple object instances in the scene, and we are interested ...
Oct 22, 2022 · We train a Spatial Transformer Network (the so called "agent") to improve the performance of a downstream classifier in the context of cluttered ...
This paper presents a technique for detection and classification of short duration voltage variations including voltage sag, swell and interruption.
Sep 30, 2022 · Sequential Spatial Transformer Networks for Salient Object Classification · Hitchhiker's Guide to Super-Resolution: Introduction and Recent ...
Oct 7, 2023 · Introduction · 1. We propose a novel optical RSIs saliency model, namely ATC-Net, to aggregate the global contextual information and the local ...
4.3, we investigate the use of multiple parallel spatial transformers for fine-grained classification, showing state-of-the-art performance on CUB-200-2011 ...
May 27, 2019 · classification task where preserving the spatial structure is ... Spatial transformer networks. In NIPS, 2015 ... saliency network for salient ...
A spatial attention mechanism based on transformer encoder is developed to capture the salient object features in images. •. A feature enhancement and ...
takes all frames as input and processes them in parallel. 265. The transformer network is optimized by using spatial-. 266 temporal adversarial losses and a ...