Domain-Specialized Object Detection via Model-Level Mixtures of Experts
Fuente:
arXiv
Saved in:
| Main Authors: | Pavlitska, Svetlana, Stüven, Malte, Keskin, Beyza, Zöllner, J. Marius |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Extracting Uncertainty Estimates from Mixtures of Experts for Semantic Segmentation
by: Pavlitska, Svetlana, et al.
Published: (2025)
by: Pavlitska, Svetlana, et al.
Published: (2025)
Towards Adversarial Robustness of Model-Level Mixture-of-Experts Architectures for Semantic Segmentation
by: Pavlitska, Svetlana, et al.
Published: (2024)
by: Pavlitska, Svetlana, et al.
Published: (2024)
Robust Experts: the Effect of Adversarial Training on CNNs with Sparse Mixture-of-Experts Layers
by: Pavlitska, Svetlana, et al.
Published: (2025)
by: Pavlitska, Svetlana, et al.
Published: (2025)
Design and Behavior of Sparse Mixture-of-Experts Layers in CNN-based Semantic Segmentation
by: Pavlitska, Svetlana, et al.
Published: (2026)
by: Pavlitska, Svetlana, et al.
Published: (2026)
Evaluating Adversarial Attacks on Traffic Sign Classifiers beyond Standard Baselines
by: Pavlitska, Svetlana, et al.
Published: (2024)
by: Pavlitska, Svetlana, et al.
Published: (2024)
Runtime Safety Monitoring of Deep Neural Networks for Perception: A Survey
by: Schotschneider, Albert, et al.
Published: (2025)
by: Schotschneider, Albert, et al.
Published: (2025)
Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light Detectors
by: Pavlitska, Svetlana, et al.
Published: (2025)
by: Pavlitska, Svetlana, et al.
Published: (2025)
TLD-READY: Traffic Light Detection -- Relevance Estimation and Deployment Analysis
by: Polley, Nikolai, et al.
Published: (2024)
by: Polley, Nikolai, et al.
Published: (2024)
UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving
by: Bogdoll, Daniel, et al.
Published: (2024)
by: Bogdoll, Daniel, et al.
Published: (2024)
DEAP DIVE: Dataset Investigation with Vision transformers for EEG evaluation
by: Hoffsommer, Annemarie, et al.
Published: (2025)
by: Hoffsommer, Annemarie, et al.
Published: (2025)
Hybrid Video Anomaly Detection for Anomalous Scenarios in Autonomous Driving
by: Bogdoll, Daniel, et al.
Published: (2024)
by: Bogdoll, Daniel, et al.
Published: (2024)
2.5D Object Detection for Intelligent Roadside Infrastructure
by: Polley, Nikolai, et al.
Published: (2025)
by: Polley, Nikolai, et al.
Published: (2025)
Conditioning Latent-Space Clusters for Real-World Anomaly Classification
by: Bogdoll, Daniel, et al.
Published: (2023)
by: Bogdoll, Daniel, et al.
Published: (2023)
Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
by: Oldfield, James, et al.
Published: (2024)
by: Oldfield, James, et al.
Published: (2024)
Iterative Filter Pruning for Concatenation-based CNN Architectures
by: Pavlitska, Svetlana, et al.
Published: (2024)
by: Pavlitska, Svetlana, et al.
Published: (2024)
Mixture-of-Experts for Open Set Domain Adaptation: A Dual-Space Detection Approach
by: Du, Zhenbang, et al.
Published: (2023)
by: Du, Zhenbang, et al.
Published: (2023)
Video Relationship Detection Using Mixture of Experts
by: Shaabana, Ala, et al.
Published: (2024)
by: Shaabana, Ala, et al.
Published: (2024)
CAGE: Circumplex Affect Guided Expression Inference
by: Wagner, Niklas, et al.
Published: (2024)
by: Wagner, Niklas, et al.
Published: (2024)
Self-Supervised Pretraining for Aerial Road Extraction
by: Polley, Rupert, et al.
Published: (2025)
by: Polley, Rupert, et al.
Published: (2025)
Merging Multi-Task Models via Weight-Ensembling Mixture of Experts
by: Tang, Anke, et al.
Published: (2024)
by: Tang, Anke, et al.
Published: (2024)
EffiComm: Bandwidth Efficient Multi Agent Communication
by: Yazgan, Melih, et al.
Published: (2025)
by: Yazgan, Melih, et al.
Published: (2025)
Scaling Continual Learning to 300+ Tasks with Bi-Level Routing Mixture-of-Experts
by: Lou, Meng, et al.
Published: (2026)
by: Lou, Meng, et al.
Published: (2026)
Segment to Focus: Guiding Latent Action Models in the Presence of Distractors
by: Fechner, Marcus, et al.
Published: (2026)
by: Fechner, Marcus, et al.
Published: (2026)
Mixture-of-Experts Models in Vision: Routing, Optimization, and Generalization
by: Rokah, Adam, et al.
Published: (2026)
by: Rokah, Adam, et al.
Published: (2026)
Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector
by: Fu, Yuqian, et al.
Published: (2024)
by: Fu, Yuqian, et al.
Published: (2024)
Towards a Systematic Risk Assessment of Deep Neural Network Limitations in Autonomous Driving Perception
by: Pavlitska, Svetlana, et al.
Published: (2026)
by: Pavlitska, Svetlana, et al.
Published: (2026)
The ATLAS of Traffic Lights: A Reliable Perception Framework for Autonomous Driving
by: Polley, Rupert, et al.
Published: (2025)
by: Polley, Rupert, et al.
Published: (2025)
Efficient Training of Diffusion Mixture-of-Experts Models: A Practical Recipe
by: Liu, Yahui, et al.
Published: (2025)
by: Liu, Yahui, et al.
Published: (2025)
Task-customized Masked AutoEncoder via Mixture of Cluster-conditional Experts
by: Liu, Zhili, et al.
Published: (2024)
by: Liu, Zhili, et al.
Published: (2024)
Measuring the Impact of Scene Level Objects on Object Detection: Towards Quantitative Explanations of Detection Decisions
by: Haar, Lynn Vonder, et al.
Published: (2024)
by: Haar, Lynn Vonder, et al.
Published: (2024)
DenseBEV: Transforming BEV Grid Cells into 3D Objects
by: Dähling, Marius, et al.
Published: (2025)
by: Dähling, Marius, et al.
Published: (2025)
Efficient and Effective Weight-Ensembling Mixture of Experts for Multi-Task Model Merging
by: Shen, Li, et al.
Published: (2024)
by: Shen, Li, et al.
Published: (2024)
MoTE: Mixture of Ternary Experts for Memory-efficient Large Multimodal Models
by: Wang, Hongyu, et al.
Published: (2025)
by: Wang, Hongyu, et al.
Published: (2025)
EMoE: Eigenbasis-Guided Routing for Mixture-of-Experts
by: Cheng, Anzhe, et al.
Published: (2026)
by: Cheng, Anzhe, et al.
Published: (2026)
Stable Routing for Mixture-of-Experts in Class-Incremental Learning
by: Guo, Zirui, et al.
Published: (2026)
by: Guo, Zirui, et al.
Published: (2026)
LPT++: Efficient Training on Mixture of Long-tailed Experts
by: Dong, Bowen, et al.
Published: (2024)
by: Dong, Bowen, et al.
Published: (2024)
Mixture of Experts in Image Classification: What's the Sweet Spot?
by: Videau, Mathurin, et al.
Published: (2024)
by: Videau, Mathurin, et al.
Published: (2024)
Robust Object Detection of Underwater Robot based on Domain Generalization
by: Song, Pinhao
Published: (2025)
by: Song, Pinhao
Published: (2025)
MoQE: Improve Quantization Model performance via Mixture of Quantization Experts
by: Zhang, Jinhao, et al.
Published: (2025)
by: Zhang, Jinhao, et al.
Published: (2025)
Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptions
by: Bogdoll, Daniel, et al.
Published: (2024)
by: Bogdoll, Daniel, et al.
Published: (2024)
Similar Items
-
Extracting Uncertainty Estimates from Mixtures of Experts for Semantic Segmentation
by: Pavlitska, Svetlana, et al.
Published: (2025) -
Towards Adversarial Robustness of Model-Level Mixture-of-Experts Architectures for Semantic Segmentation
by: Pavlitska, Svetlana, et al.
Published: (2024) -
Robust Experts: the Effect of Adversarial Training on CNNs with Sparse Mixture-of-Experts Layers
by: Pavlitska, Svetlana, et al.
Published: (2025) -
Design and Behavior of Sparse Mixture-of-Experts Layers in CNN-based Semantic Segmentation
by: Pavlitska, Svetlana, et al.
Published: (2026) -
Evaluating Adversarial Attacks on Traffic Sign Classifiers beyond Standard Baselines
by: Pavlitska, Svetlana, et al.
Published: (2024)