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08/18/2023
Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers
The growing popularity of Vision Transformers as the go-to models for im...
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08/15/2023
YODA: You Only Diffuse Areas. An Area-Masked Diffusion Approach For Image Super-Resolution
This work introduces "You Only Diffuse Areas" (YODA), a novel method for...
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07/10/2023
DWA: Differential Wavelet Amplifier for Image Super-Resolution
This work introduces Differential Wavelet Amplifier (DWA), a drop-in mod...
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04/04/2023
Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-Resolution
This paper presents a novel Diffusion-Wavelet (DiWa) approach for Single...
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09/27/2022
Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances
With the advent of Deep Learning (DL), Super-Resolution (SR) has also be...
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08/22/2021
Spatial Transformer Networks for Curriculum Learning
Curriculum learning is a bio-inspired training technique that is widely ...
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05/14/2021
XAI Handbook: Towards a Unified Framework for Explainable AI
The field of explainable AI (XAI) has quickly become a thriving and prol...
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01/07/2021
Contextual Classification Using Self-Supervised Auxiliary Models for Deep Neural Networks
Classification problems solved with deep neural networks (DNNs) typicall...
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04/25/2020
Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory
Video Object Segmentation (VOS) is an active research area of the visual...
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03/26/2020
P ≈ NP, at least in Visual Question Answering
In recent years, progress in the Visual Question Answering (VQA) field h...
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03/22/2018
What do Deep Networks Like to See?
We propose a novel way to measure and understand convolutional neural ne...
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03/21/2018