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07/05/2023
RADiff: Controllable Diffusion Models for Radio Astronomical Maps Generation
Along with the nearing completion of the Square Kilometre Array (SKA), c...
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06/12/2023
Learning to Mask and Permute Visual Tokens for Vision Transformer Pre-Training
The use of self-supervised pre-training has emerged as a promising appro...
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03/28/2023
Reproducibility is Nothing without Correctness: The Importance of Testing Code in NLP
Despite its pivotal role in research experiments, code correctness is of...
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02/13/2023
Fixing Overconfidence in Dynamic Neural Networks
Dynamic neural networks are a recent technique that promises a remedy fo...
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11/01/2022
Expansion of Visual Hints for Improved Generalization in Stereo Matching
We introduce visual hints expansion for guiding stereo matching to impro...
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08/16/2022
Uncertainty-guided Source-free Domain Adaptation
Source-free domain adaptation (SFDA) aims to adapt a classifier to an un...
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05/27/2022
A Look at Improving Robustness in Visual-inertial SLAM by Moment Matching
The fusion of camera sensor and inertial data is a leading method for eg...
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09/17/2019
Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled Networks
Recent deep monocular depth estimation approaches based on supervised re...
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08/15/2019
Structured Coupled Generative Adversarial Networks for Unsupervised Monocular Depth Estimation
Inspired by the success of adversarial learning, we propose a new end-to...
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04/17/2019
Online Adaptation through Meta-Learning for Stereo Depth Estimation
In this work, we tackle the problem of online adaptation for stereo dept...
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03/11/2019
Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation
Nowadays, the majority of state of the art monocular depth estimation te...
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07/28/2018
Unsupervised Adversarial Depth Estimation using Cycled Generative Networks
While recent deep monocular depth estimation approaches based on supervi...
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03/11/2017