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Found 12 papers, 4 papers with code
TUMTraf V2X Cooperative Perception Dataset
We propose CoopDet3D, a cooperative multi-modal fusion model, and TUMTraf-V2X, a perception dataset, for the cooperative 3D object detection and tracking task.
ActiveAnno3D - An Active Learning Framework for Multi-Modal 3D Object Detection
We propose ActiveAnno3D, an active learning framework to select data samples for labeling that are of maximum informativeness for training.
GPT-4V as Traffic Assistant: An In-depth Look at Vision Language Model on Complex Traffic Events
The recognition and understanding of traffic incidents, particularly traffic accidents, is a topic of paramount importance in the realm of intelligent transportation systems and intelligent vehicles.
TUMTraf Event: Calibration and Fusion Resulting in a Dataset for Roadside Event-Based and RGB Cameras
To the best of our knowledge, no targetless calibration between event-based and RGB cameras can handle multiple moving objects, nor does data fusion optimized for the domain of roadside ITS exist.
A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlook
Autonomous driving has rapidly developed and shown promising performance due to recent advances in hardware and deep learning techniques.
Vision Language Models in Autonomous Driving and Intelligent Transportation Systems
The applications of Vision-Language Models (VLMs) in the fields of Autonomous Driving (AD) and Intelligent Transportation Systems (ITS) have attracted widespread attention due to their outstanding performance and the ability to leverage Large Language Models (LLMs).
3D Understanding of Deformable Linear Objects: Datasets and Transferability Benchmark
Finally, we analyzed the generalization capabilities of these methods by conducting transferability experiments on the PointWire and PointVessel datasets.
Multi-Task Consistency for Active Learning
In single-task vision-based settings, inconsistency-based active learning has proven to be effective in selecting informative samples for annotation.
A9 Intersection Dataset: All You Need for Urban 3D Camera-LiDAR Roadside Perception
Our dataset consists of 4. 8k images and point clouds with more than 57. 4k manually labeled 3D boxes.
InfraDet3D: Multi-Modal 3D Object Detection based on Roadside Infrastructure Camera and LiDAR Sensors
We evaluate our results on the A9 infrastructure dataset and achieve 68. 48 mAP on the test set.
Real-Time And Robust 3D Object Detection with Roadside LiDARs
This work aims to address the challenges in autonomous driving by focusing on the 3D perception of the environment using roadside LiDARs.
Scalability in Neural Control of Musculoskeletal Robots
Anthropomimetic robots are robots that sense, behave, interact and feel like humans.
