A CLIP-based Uncertainty Modal Modeling (UMM) Framework for Pedestrian Re-Identification in Autonomous Driving
Fuente:
arXiv
Guardado en:
| Autores principales: | Li, Jialin, Wu, Shuqi, Wang, Ning |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Modality Unified Attack for Omni-Modality Person Re-Identification
por: Bian, Yuan, et al.
Publicado: (2025)
por: Bian, Yuan, et al.
Publicado: (2025)
Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving
por: Gao, Haoxiang, et al.
Publicado: (2025)
por: Gao, Haoxiang, et al.
Publicado: (2025)
SCaRL- A Synthetic Multi-Modal Dataset for Autonomous Driving
por: Ramesh, Avinash Nittur, et al.
Publicado: (2024)
por: Ramesh, Avinash Nittur, et al.
Publicado: (2024)
A Safety-Adapted Loss for Pedestrian Detection in Automated Driving
por: Lyssenko, Maria, et al.
Publicado: (2024)
por: Lyssenko, Maria, et al.
Publicado: (2024)
RMT-PPAD: Real-time Multi-task Learning for Panoptic Perception in Autonomous Driving
por: Wang, Jiayuan, et al.
Publicado: (2025)
por: Wang, Jiayuan, et al.
Publicado: (2025)
Gating Syn-to-Real Knowledge for Pedestrian Crossing Prediction in Safe Driving
por: Bai, Jie, et al.
Publicado: (2024)
por: Bai, Jie, et al.
Publicado: (2024)
Multi-Modal Sensor Fusion using Hybrid Attention for Autonomous Driving
por: Mayank, Mayank, et al.
Publicado: (2026)
por: Mayank, Mayank, et al.
Publicado: (2026)
Attention Deep Model with Multi-Scale Deep Supervision for Person Re-Identification
por: Wu, Di, et al.
Publicado: (2019)
por: Wu, Di, et al.
Publicado: (2019)
A Survey for Foundation Models in Autonomous Driving
por: Gao, Haoxiang, et al.
Publicado: (2024)
por: Gao, Haoxiang, et al.
Publicado: (2024)
Group-CLIP Uncertainty Modeling for Group Re-Identification
por: Zhang, Qingxin, et al.
Publicado: (2025)
por: Zhang, Qingxin, et al.
Publicado: (2025)
The ATLAS of Traffic Lights: A Reliable Perception Framework for Autonomous Driving
por: Polley, Rupert, et al.
Publicado: (2025)
por: Polley, Rupert, et al.
Publicado: (2025)
Beyond Pedestrians: Caption-Guided CLIP Framework for High-Difficulty Video-based Person Re-Identification
por: Hamano, Shogo, et al.
Publicado: (2026)
por: Hamano, Shogo, et al.
Publicado: (2026)
CountCLIP -- [Re] Teaching CLIP to Count to Ten
por: Mestha, Harshvardhan, et al.
Publicado: (2024)
por: Mestha, Harshvardhan, et al.
Publicado: (2024)
Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous Driving
por: Kong, Lingdong, et al.
Publicado: (2024)
por: Kong, Lingdong, et al.
Publicado: (2024)
An Individual Identity-Driven Framework for Animal Re-Identification
por: Wu, Yihao, et al.
Publicado: (2024)
por: Wu, Yihao, et al.
Publicado: (2024)
Generative Adversarial Patches for Physical Attacks on Cross-Modal Pedestrian Re-Identification
por: Su, Yue, et al.
Publicado: (2024)
por: Su, Yue, et al.
Publicado: (2024)
SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving
por: Cortinhal, Tiago, et al.
Publicado: (2020)
por: Cortinhal, Tiago, et al.
Publicado: (2020)
World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving
por: Guan, Yanchen, et al.
Publicado: (2025)
por: Guan, Yanchen, et al.
Publicado: (2025)
MetaWild: A Multimodal Dataset for Animal Re-Identification with Environmental Metadata
por: Li, Yuzhuo, et al.
Publicado: (2025)
por: Li, Yuzhuo, et al.
Publicado: (2025)
PFM-VEPAR: Prompting Foundation Models for RGB-Event Camera based Pedestrian Attribute Recognition
por: Xu, Minghe, et al.
Publicado: (2026)
por: Xu, Minghe, et al.
Publicado: (2026)
Mind the Gap: Preserving and Compensating for the Modality Gap in CLIP-Based Continual Learning
por: Huang, Linlan, et al.
Publicado: (2025)
por: Huang, Linlan, et al.
Publicado: (2025)
Panoptic Perception for Autonomous Driving: A Survey
por: Li, Yunge, et al.
Publicado: (2024)
por: Li, Yunge, et al.
Publicado: (2024)
When Person Re-Identification Meets Event Camera: A Benchmark Dataset and An Attribute-guided Re-Identification Framework
por: Wang, Xiao, et al.
Publicado: (2025)
por: Wang, Xiao, et al.
Publicado: (2025)
Breaking the Limits of Open-Weight CLIP: An Optimization Framework for Self-supervised Fine-tuning of CLIP
por: Mehta, Anant, et al.
Publicado: (2026)
por: Mehta, Anant, et al.
Publicado: (2026)
Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting
por: Tang, Bohan, et al.
Publicado: (2022)
por: Tang, Bohan, et al.
Publicado: (2022)
A Flow-based Credibility Metric for Safety-critical Pedestrian Detection
por: Lyssenko, Maria, et al.
Publicado: (2024)
por: Lyssenko, Maria, et al.
Publicado: (2024)
Universal Camouflage Attack on Vision-Language Models for Autonomous Driving
por: Kong, Dehong, et al.
Publicado: (2025)
por: Kong, Dehong, et al.
Publicado: (2025)
Learning Informative Attention Weights for Person Re-Identification
por: Wang, Yancheng, et al.
Publicado: (2025)
por: Wang, Yancheng, et al.
Publicado: (2025)
MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training
por: Vasu, Pavan Kumar Anasosalu, et al.
Publicado: (2023)
por: Vasu, Pavan Kumar Anasosalu, et al.
Publicado: (2023)
Toward Modality Gap: Vision Prototype Learning for Weakly-supervised Semantic Segmentation with CLIP
por: Xu, Zhongxing, et al.
Publicado: (2024)
por: Xu, Zhongxing, et al.
Publicado: (2024)
Embedding Compression for Efficient Re-Identification
por: McDermott, Luke
Publicado: (2024)
por: McDermott, Luke
Publicado: (2024)
MoP-CLIP: A Mixture of Prompt-Tuned CLIP Models for Domain Incremental Learning
por: Nicolas, Julien, et al.
Publicado: (2023)
por: Nicolas, Julien, et al.
Publicado: (2023)
External Knowledge Injection for CLIP-Based Class-Incremental Learning
por: Zhou, Da-Wei, et al.
Publicado: (2025)
por: Zhou, Da-Wei, et al.
Publicado: (2025)
Bridging Modalities via Progressive Re-alignment for Multimodal Test-Time Adaptation
por: Li, Jiacheng, et al.
Publicado: (2025)
por: Li, Jiacheng, et al.
Publicado: (2025)
Road Boundary Detection Using 4D mmWave Radar for Autonomous Driving
por: Wu, Yuyan, et al.
Publicado: (2025)
por: Wu, Yuyan, et al.
Publicado: (2025)
UGG-ReID: Uncertainty-Guided Graph Model for Multi-Modal Object Re-Identification
por: Wan, Xixi, et al.
Publicado: (2025)
por: Wan, Xixi, et al.
Publicado: (2025)
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving
por: Xing, Shuo, et al.
Publicado: (2024)
por: Xing, Shuo, et al.
Publicado: (2024)
SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving
por: Wang, Wenjing, et al.
Publicado: (2026)
por: Wang, Wenjing, et al.
Publicado: (2026)
Exploiting T-norms for Deep Learning in Autonomous Driving
por: Stoian, Mihaela Cătălina, et al.
Publicado: (2024)
por: Stoian, Mihaela Cătălina, et al.
Publicado: (2024)
From Parameter to Representation: A Closed-Form Approach for Controllable Model Merging
por: Wu, Jialin, et al.
Publicado: (2025)
por: Wu, Jialin, et al.
Publicado: (2025)
Ejemplares similares
-
Modality Unified Attack for Omni-Modality Person Re-Identification
por: Bian, Yuan, et al.
Publicado: (2025) -
Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving
por: Gao, Haoxiang, et al.
Publicado: (2025) -
SCaRL- A Synthetic Multi-Modal Dataset for Autonomous Driving
por: Ramesh, Avinash Nittur, et al.
Publicado: (2024) -
A Safety-Adapted Loss for Pedestrian Detection in Automated Driving
por: Lyssenko, Maria, et al.
Publicado: (2024) -
RMT-PPAD: Real-time Multi-task Learning for Panoptic Perception in Autonomous Driving
por: Wang, Jiayuan, et al.
Publicado: (2025)