arXiv Computer Vision

Front-to-Back: Benchmarking Vision-Language Models for Asymmetric Cross-View Vehicle Re-Identification

arXiv Machine Learning

Jun 9

Zero-Shot Semantic Re-Identification for Autonomous Driving: A VLM Baseline Study

arXiv:2606. 09362v1 Announce Type: cross Abstract: Re-Identification (ReID) in autonomous driving is typically formulated as a visual matching problem, where observations of vehicles, pedestrians, and cyclists are associated across time, frames, or camera views using learned appearance embeddings, often complemented by motion, geometric, or multimodal cues.

By Eduardo Borges, Manuel Abreu, Lu\'is Garrote, Urbano J. Nunes

llms rag agents robotics multimodal benchmarks safety

arXiv Computer Vision

Sep 2

A Benchmark for Vehicle Attribute Classification in Cross-Domain Surveillance Scenarios

arXiv:2609.01584v1 Announce Type: new Abstract: Vehicle attribute analysis is a key component of Intelligent Transportation Systems (ITS), supporting applications such as vehicle identification, traf...

By Sergio M. Silva Jr., Otavio T. Remer, Gabriel E. Lima, Lucas Wojcik, Rayson Laroca, David Menotti

benchmarks

arXiv AI

Sep 15

A Generative AI Integrated Multimodal Framework for Low-Latency Multi-Camera Person Re-Identification

arXiv:2609.14419v1 Announce Type: cross Abstract: Person re-identification (ReID) is essential for multi-camera surveillance and tracking, yet remains difficult due to viewpoint and illumination chan...

By Leon Fernando, C Dombawala, P. Hettigoda, Vanodhya G. Warnasooriya, Ishara Neranjana, Rashmika Nawaratne

llms rag multimodal benchmarks

arXiv Machine Learning

Jun 4

An Open-Source Two-Stage Computer Vision Pipeline for Fine-Grained Vehicle Classification using Vision Transformers

arXiv:2606. 05149v1 Announce Type: cross Abstract: Vehicle body type is a significant determinant of cyclist injury severity in overtaking crashes, yet automated tools for classifying vehicles into injury-risk-relevant categories from naturalistic roadway video do not exist in the open literature.

By Gandhimathi Padmanaban, Fred Feng

llms computer-vision fine-tuning benchmarks safety

arXiv Computer Vision

Sep 10

VANTAGE-Bench: Evaluating the Infrastructure AI Gap in Vision-Language Models

arXiv:2609.09396v1 Announce Type: new Abstract: As Vision-Language Models (VLMs) advance toward physical deployment, the focus has remained on action-oriented Embodied AI evaluated on subject-centric...

By Zaid Pervaiz Bhat, Nimra Nayyar, Arihant Jain, Lap Fung Chan, John Suchanek, Yu Wang, Varun Praveen, Tomasz Kornuta, Vidya Nariyambut Murali

llms nlp robotics multimodal benchmarks safety

arXiv AI

Jun 9

Cross-View Urban Traffic Dataset: Drone-Supervised Ground Truth for Monocular Bird's-Eye View Localization

arXiv:2606. 07708v1 Announce Type: cross Abstract: We introduce a dataset and benchmark for cross-view urban traffic perception built from synchronized ego-centric bicycle videos and aerial drone videos recorded at real urban intersections.

By Prakhar Bhardwaj, Simone Weikl, Kilian Mang, Elia Jonas Sandtner

robotics benchmarks safety

arXiv Computer Vision

Aug 31

A-PAIR: A Benchmark and Identity-Consistent Grounding Framework for Air-Ground Cross-View Referring Person Detection

arXiv:2608.27997v1 Announce Type: new Abstract: Air-ground cross-view referring person detection is a necessary component in the language-to-perception-to-control chain of collective embodied intelli...

By Zhoupeng Guo, Xinjie Yao, Yunqi Zhu, Zhihe Fan, Siqi Zhao, Jianjun Chen, Yichen Dong, Yan Fan, Pengfei Zhu

agents robotics benchmarks safety

Hugging Face Trending Papers

Jul 2

Evaluating Vision-Language Models as a Zero-Shot Learning Alternative to You Only Look Once and Optical Character Recognition for Nigerian License Plate Recognition

License Plate Recognition (LPR) systems are critical tools in traffic monitoring, security enforcement, and urban mobility management. Traditional LPR systems often rely on a multi-stage pipeline involving object detection using You Only Look Once (YOLO) and Optical Character Recognition (OCR), which suffer from limitations such as high resource demands, poor performance in unstructured environments, and the need for large annotated datasets.

llms computer-vision multimodal

arXiv AI

Jun 9

Decoding Pedestrian Crossing Intention from Egocentric Vision via Vision Language Models

arXiv:2606. 09142v1 Announce Type: cross Abstract: Egocentric vision offers a first-person view of human perception and decision making, yet its potential for traffic-safety prediction remains underexplored.

By Danya Li, Xiang Su, Yan Feng, Rico Krueger

llms nlp fine-tuning benchmarks safety

arXiv Computer Vision

Sep 1

Evaluating 2D and 3D-Aware Vision Foundation Models for Vehicle Attribute Recognition

arXiv:2608.29929v1 Announce Type: new Abstract: Vehicle attribute recognition is an important task in intelligent transportation systems, particularly when Automatic License Plate Recognition (ALPR)...

By Alexandre V. Delazeri, Gabriel E. Lima, Eduil Nascimento Jr, Rayson Laroca, David Menotti

benchmarks

arXiv Computer Vision

Sep 22

Seeing is not Enough: Vision-Language Models Perceive Evidence but Fail to Act

arXiv:2609.22588v1 Announce Type: new Abstract: Vision-language models (VLMs) perform strongly on visual question answering benchmarks, yet often make decisions that contradict visual evidence they h...

By Yuyang Dai, Bofei Huang, Hongbo Zhang, Haoran Xie

llms nlp multimodal benchmarks

arXiv Computer Vision

Aug 25

ENCORE: Entropy-Guided Cropping and Attention Regularization for Robust Vision--Language Understanding

arXiv:2608.22996v1 Announce Type: new Abstract: Vision-Language Models (VLMs) perform well on diverse vision-language tasks, but transformer-based visual encoders split images into fixed-resolution s...

By Yuanhao Sun, Huawei Ji, Jiaxin Ding, Luoyi Fu, Xinbing Wang

llms fine-tuning multimodal benchmarks

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