Imagen de Portada

Evaluating the Adversarial Robustness of Semantic Segmentation: Trying Harder Pays Off

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Halmosi, Levente, Mohos, Bálint, Jelasity, Márk
Formato:	Preprint
Publicado:	2024
Materias:	Computer Vision and Pattern Recognition Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation
por: Xie, Zhengyuan, et al.
Publicado: (2024)

Evaluating the Robustness of Off-Road Autonomous Driving Segmentation against Adversarial Attacks: A Dataset-Centric analysis
por: Deoli, Pankaj, et al.
Publicado: (2024)

Towards Adversarial Robustness of Model-Level Mixture-of-Experts Architectures for Semantic Segmentation
por: Pavlitska, Svetlana, et al.
Publicado: (2024)

Towards Reliable Evaluation and Fast Training of Robust Semantic Segmentation Models
por: Croce, Francesco, et al.
Publicado: (2023)

Evaluating the Adversarial Robustness of Detection Transformers
por: Nazeri, Amirhossein, et al.
Publicado: (2024)

TsallisPGD: Adaptive Gradient Weighting for Adversarial Attacks on Semantic Segmentation
por: Matyasko, Alexander, et al.
Publicado: (2026)

Pay Attention to the Atlas: Atlas-Guided Test-Time Adaptation Method for Robust 3D Medical Image Segmentation
por: Guo, Jingjie, et al.
Publicado: (2023)

Learning to Generate Training Datasets for Robust Semantic Segmentation
por: Hariat, Marwane, et al.
Publicado: (2023)

RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-plane Networks
por: Ghosh, Partha, et al.
Publicado: (2024)

Overcoming Support Dilution for Robust Few-shot Semantic Segmentation
por: Tang, Wailing, et al.
Publicado: (2025)

Few-shot Semantic Learning for Robust Multi-Biome 3D Semantic Mapping in Off-Road Environments
por: Atha, Deegan, et al.
Publicado: (2024)

Voost: A Unified and Scalable Diffusion Transformer for Bidirectional Virtual Try-On and Try-Off
por: Lee, Seungyong, et al.
Publicado: (2025)

FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation Methods
por: Khorzooghi, Seyyed Mohammad Sadegh Moosavi, et al.
Publicado: (2025)

Learning Ordinality in Semantic Segmentation
por: Cruz, Ricardo P. M., et al.
Publicado: (2024)

Noisy Annotations in Semantic Segmentation
por: Kimhi, Moshe, et al.
Publicado: (2024)

Enhancing Adversarial Robustness via Uncertainty-Aware Distributional Adversarial Training
por: Dong, Junhao, et al.
Publicado: (2024)

DSV-LFS: Unifying LLM-Driven Semantic Cues with Visual Features for Robust Few-Shot Segmentation
por: Karimi, Amin, et al.
Publicado: (2025)

Dynamic Label Adversarial Training for Deep Learning Robustness Against Adversarial Attacks
por: Liu, Zhenyu, et al.
Publicado: (2024)

Medical Semantic Segmentation with Diffusion Pretrain
por: Li, David, et al.
Publicado: (2025)

When Does Supervised Training Pay Off? The Hidden Economics of Object Detection in the Era of Vision-Language Models
por: Al-Hamadani, Samer
Publicado: (2025)

Adaptive Batch Normalization Networks for Adversarial Robustness
por: Lo, Shao-Yuan, et al.
Publicado: (2024)

Compositional Adversarial Training for Robust Visual Watermarking
por: Satheesh, Anirudh, et al.
Publicado: (2026)

Single Image Inpainting and Super-Resolution with Simultaneous Uncertainty Guarantees by Universal Reproducing Kernels
por: Horváth, Bálint, et al.
Publicado: (2025)

Exploring Simple Open-Vocabulary Semantic Segmentation
por: Lai, Zihang
Publicado: (2024)

Adversarially Robust CLIP Models Can Induce Better (Robust) Perceptual Metrics
por: Croce, Francesco, et al.
Publicado: (2025)

MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
por: Reza, Md Kaykobad, et al.
Publicado: (2023)

Revisiting Generative Adversarial Networks for Binary Semantic Segmentation on Imbalanced Datasets
por: Xu, Lei, et al.
Publicado: (2024)

Segmentation by Factorization: Unsupervised Semantic Segmentation for Pathology by Factorizing Foundation Model Features
por: Gildenblat, Jacob, et al.
Publicado: (2024)

Evaluation of Deep Learning Semantic Segmentation for Land Cover Mapping on Multispectral, Hyperspectral and High Spatial Aerial Imagery
por: Panuntun, Ilham Adi, et al.
Publicado: (2024)

Towards Adversarially Robust Dataset Distillation by Curvature Regularization
por: Xue, Eric, et al.
Publicado: (2024)

Narrowing Class-Wise Robustness Gaps in Adversarial Training
por: Amerehi, Fatemeh, et al.
Publicado: (2025)

Improving Adversarial Robustness of Attribution via Implicit Regularization
por: Mehrpanah, Amir, et al.
Publicado: (2026)

Which Models have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
por: Srinivas, Suraj, et al.
Publicado: (2023)

Revisiting Semi-supervised Adversarial Robustness via Noise-aware Online Robust Distillation
por: Wu, Tsung-Han, et al.
Publicado: (2024)

The Influence of Faulty Labels in Data Sets on Human Pose Estimation
por: Schwarz, Arnold, et al.
Publicado: (2024)

On Efficient Real-Time Semantic Segmentation: A Survey
por: Holder, Christopher J., et al.
Publicado: (2022)

Distilling Knowledge from Heterogeneous Architectures for Semantic Segmentation
por: Huang, Yanglin, et al.
Publicado: (2025)

FLOSS: Free Lunch in Open-vocabulary Semantic Segmentation
por: Benigmim, Yasser, et al.
Publicado: (2025)

3D Semantic Segmentation for Post-Disaster Assessment
por: Le, Nhut, et al.
Publicado: (2025)

Framework-agnostic Semantically-aware Global Reasoning for Segmentation
por: Hossain, Mir Rayat Imtiaz, et al.
Publicado: (2022)