SegMix: Co-occurrence Driven Mixup for Semantic Segmentation and Adversarial Robustness

23 August 2021

Papers citing "SegMix: Co-occurrence Driven Mixup for Semantic Segmentation and Adversarial Robustness"

7 / 7 papers shown

Title
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning F. Mumuni A. Mumuni AAML 39 5 0 11 Mar 2024
Tailoring Mixup to Data for Calibration Quentin Bouniot Pavlo Mozharovskyi Florence dÁlché-Buc 61 1 0 02 Nov 2023
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup Damien Teney Jindong Wang Ehsan Abbasnejad 35 6 0 26 May 2023
GAMA: Generative Adversarial Multi-Object Scene Attacks Abhishek Aich Calvin-Khang Ta Akash Gupta Chengyu Song S. Krishnamurthy Ulugbek S. Kamilov Amit K. Roy-Chowdhury AAML 53 17 0 20 Sep 2022
Survey: Image Mixing and Deleting for Data Augmentation Humza Naveed Saeed Anwar Munawar Hayat Kashif Javed Ajmal Mian 42 78 0 13 Jun 2021
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 326 5,847 0 08 Jul 2016
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 451 15,652 0 02 Nov 2015