19 citations · 21 across the 7 of their papers we have counts for
7 papers
Supervised Fine-tuning Evaluation for Long-term Visual Place Recognition
Farid Alijani, Esa Rahtu
In this paper, we present a comprehensive study on the utility of deep convolutional neural networks with two state-of-the-art pooling layers which are placed after convolutional l…
Sparse in Space and Time: Audio-visual Synchronisation with Trainable Selectors
Vladimir Iashin, Weidi Xie, Esa Rahtu +1
The objective of this paper is audio-visual synchronisation of general videos 'in the wild'. For such videos, the events that may be harnessed for synchronisation cues may be spati…
Taming Visually Guided Sound Generation
Vladimir Iashin, Esa Rahtu
Recent advances in visually-induced audio generation are based on sampling short, low-fidelity, and one-class sounds. Moreover, sampling 1 second of audio from the state-of-the-art…
V-SlowFast Network for Efficient Visual Sound Separation
Lingyu Zhu, Esa Rahtu
The objective of this paper is to perform visual sound separation: i) we study visual sound separation on spectrograms of different temporal resolutions; ii) we propose a new light…
Lightweight Monocular Depth with a Novel Neural Architecture Search Method
Lam Huynh, Phong Nguyen, Jiri Matas +2
This paper presents a novel neural architecture search method, called LiDNAS, for generating lightweight monocular depth estimation models. Unlike previous neural architecture sear…
Monocular Depth Estimation Primed by Salient Point Detection and Normalized Hessian Loss
Lam Huynh, Matteo Pedone, Phong Nguyen +3
Deep neural networks have recently thrived on single image depth estimation. That being said, current developments on this topic highlight an apparent compromise between accuracy a…