A CLIP-based Uncertainty Modal Modeling (UMM) Framework for Pedestrian Re-Identification in Autonomous Driving
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Jialin, Wu, Shuqi, Wang, Ning |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Modality Unified Attack for Omni-Modality Person Re-Identification
by: Bian, Yuan, et al.
Published: (2025)
by: Bian, Yuan, et al.
Published: (2025)
Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving
by: Gao, Haoxiang, et al.
Published: (2025)
by: Gao, Haoxiang, et al.
Published: (2025)
SCaRL- A Synthetic Multi-Modal Dataset for Autonomous Driving
by: Ramesh, Avinash Nittur, et al.
Published: (2024)
by: Ramesh, Avinash Nittur, et al.
Published: (2024)
A Safety-Adapted Loss for Pedestrian Detection in Automated Driving
by: Lyssenko, Maria, et al.
Published: (2024)
by: Lyssenko, Maria, et al.
Published: (2024)
RMT-PPAD: Real-time Multi-task Learning for Panoptic Perception in Autonomous Driving
by: Wang, Jiayuan, et al.
Published: (2025)
by: Wang, Jiayuan, et al.
Published: (2025)
Gating Syn-to-Real Knowledge for Pedestrian Crossing Prediction in Safe Driving
by: Bai, Jie, et al.
Published: (2024)
by: Bai, Jie, et al.
Published: (2024)
Multi-Modal Sensor Fusion using Hybrid Attention for Autonomous Driving
by: Mayank, Mayank, et al.
Published: (2026)
by: Mayank, Mayank, et al.
Published: (2026)
Attention Deep Model with Multi-Scale Deep Supervision for Person Re-Identification
by: Wu, Di, et al.
Published: (2019)
by: Wu, Di, et al.
Published: (2019)
A Survey for Foundation Models in Autonomous Driving
by: Gao, Haoxiang, et al.
Published: (2024)
by: Gao, Haoxiang, et al.
Published: (2024)
Group-CLIP Uncertainty Modeling for Group Re-Identification
by: Zhang, Qingxin, et al.
Published: (2025)
by: Zhang, Qingxin, et al.
Published: (2025)
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)
Beyond Pedestrians: Caption-Guided CLIP Framework for High-Difficulty Video-based Person Re-Identification
by: Hamano, Shogo, et al.
Published: (2026)
by: Hamano, Shogo, et al.
Published: (2026)
CountCLIP -- [Re] Teaching CLIP to Count to Ten
by: Mestha, Harshvardhan, et al.
Published: (2024)
by: Mestha, Harshvardhan, et al.
Published: (2024)
Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous Driving
by: Kong, Lingdong, et al.
Published: (2024)
by: Kong, Lingdong, et al.
Published: (2024)
An Individual Identity-Driven Framework for Animal Re-Identification
by: Wu, Yihao, et al.
Published: (2024)
by: Wu, Yihao, et al.
Published: (2024)
Generative Adversarial Patches for Physical Attacks on Cross-Modal Pedestrian Re-Identification
by: Su, Yue, et al.
Published: (2024)
by: Su, Yue, et al.
Published: (2024)
SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving
by: Cortinhal, Tiago, et al.
Published: (2020)
by: Cortinhal, Tiago, et al.
Published: (2020)
World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving
by: Guan, Yanchen, et al.
Published: (2025)
by: Guan, Yanchen, et al.
Published: (2025)
MetaWild: A Multimodal Dataset for Animal Re-Identification with Environmental Metadata
by: Li, Yuzhuo, et al.
Published: (2025)
by: Li, Yuzhuo, et al.
Published: (2025)
PFM-VEPAR: Prompting Foundation Models for RGB-Event Camera based Pedestrian Attribute Recognition
by: Xu, Minghe, et al.
Published: (2026)
by: Xu, Minghe, et al.
Published: (2026)
Mind the Gap: Preserving and Compensating for the Modality Gap in CLIP-Based Continual Learning
by: Huang, Linlan, et al.
Published: (2025)
by: Huang, Linlan, et al.
Published: (2025)
Panoptic Perception for Autonomous Driving: A Survey
by: Li, Yunge, et al.
Published: (2024)
by: Li, Yunge, et al.
Published: (2024)
When Person Re-Identification Meets Event Camera: A Benchmark Dataset and An Attribute-guided Re-Identification Framework
by: Wang, Xiao, et al.
Published: (2025)
by: Wang, Xiao, et al.
Published: (2025)
Breaking the Limits of Open-Weight CLIP: An Optimization Framework for Self-supervised Fine-tuning of CLIP
by: Mehta, Anant, et al.
Published: (2026)
by: Mehta, Anant, et al.
Published: (2026)
Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting
by: Tang, Bohan, et al.
Published: (2022)
by: Tang, Bohan, et al.
Published: (2022)
A Flow-based Credibility Metric for Safety-critical Pedestrian Detection
by: Lyssenko, Maria, et al.
Published: (2024)
by: Lyssenko, Maria, et al.
Published: (2024)
Universal Camouflage Attack on Vision-Language Models for Autonomous Driving
by: Kong, Dehong, et al.
Published: (2025)
by: Kong, Dehong, et al.
Published: (2025)
Learning Informative Attention Weights for Person Re-Identification
by: Wang, Yancheng, et al.
Published: (2025)
by: Wang, Yancheng, et al.
Published: (2025)
MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training
by: Vasu, Pavan Kumar Anasosalu, et al.
Published: (2023)
by: Vasu, Pavan Kumar Anasosalu, et al.
Published: (2023)
Toward Modality Gap: Vision Prototype Learning for Weakly-supervised Semantic Segmentation with CLIP
by: Xu, Zhongxing, et al.
Published: (2024)
by: Xu, Zhongxing, et al.
Published: (2024)
Embedding Compression for Efficient Re-Identification
by: McDermott, Luke
Published: (2024)
by: McDermott, Luke
Published: (2024)
MoP-CLIP: A Mixture of Prompt-Tuned CLIP Models for Domain Incremental Learning
by: Nicolas, Julien, et al.
Published: (2023)
by: Nicolas, Julien, et al.
Published: (2023)
External Knowledge Injection for CLIP-Based Class-Incremental Learning
by: Zhou, Da-Wei, et al.
Published: (2025)
by: Zhou, Da-Wei, et al.
Published: (2025)
Bridging Modalities via Progressive Re-alignment for Multimodal Test-Time Adaptation
by: Li, Jiacheng, et al.
Published: (2025)
by: Li, Jiacheng, et al.
Published: (2025)
Road Boundary Detection Using 4D mmWave Radar for Autonomous Driving
by: Wu, Yuyan, et al.
Published: (2025)
by: Wu, Yuyan, et al.
Published: (2025)
UGG-ReID: Uncertainty-Guided Graph Model for Multi-Modal Object Re-Identification
by: Wan, Xixi, et al.
Published: (2025)
by: Wan, Xixi, et al.
Published: (2025)
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving
by: Xing, Shuo, et al.
Published: (2024)
by: Xing, Shuo, et al.
Published: (2024)
SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving
by: Wang, Wenjing, et al.
Published: (2026)
by: Wang, Wenjing, et al.
Published: (2026)
Exploiting T-norms for Deep Learning in Autonomous Driving
by: Stoian, Mihaela Cătălina, et al.
Published: (2024)
by: Stoian, Mihaela Cătălina, et al.
Published: (2024)
From Parameter to Representation: A Closed-Form Approach for Controllable Model Merging
by: Wu, Jialin, et al.
Published: (2025)
by: Wu, Jialin, et al.
Published: (2025)
Similar Items
-
Modality Unified Attack for Omni-Modality Person Re-Identification
by: Bian, Yuan, et al.
Published: (2025) -
Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving
by: Gao, Haoxiang, et al.
Published: (2025) -
SCaRL- A Synthetic Multi-Modal Dataset for Autonomous Driving
by: Ramesh, Avinash Nittur, et al.
Published: (2024) -
A Safety-Adapted Loss for Pedestrian Detection in Automated Driving
by: Lyssenko, Maria, et al.
Published: (2024) -
RMT-PPAD: Real-time Multi-task Learning for Panoptic Perception in Autonomous Driving
by: Wang, Jiayuan, et al.
Published: (2025)