Nov 13, 2024 · To this end, we present V2X-R, the first simulated V2X dataset incorporating LiDAR, camera, and 4D radar. V2X-R contains 12,079 scenarios with 37,727 frames of LiDAR …

The first V2X dataset incorporates LiDAR, camera, and 4D radar. V2X-R contains 12,079 scenarios with 37,727 frames of LiDAR and 4D radar point clouds, 150,908 images, and …

V2X-Real is the first large-scale real-world dataset for Vehicle-to-Everything (V2X) cooperative perception. Multiple connected agents with two vehicles and two infrastructures, providing …

Jan 4, 2025 · V2X-DGPE employs a Knowledge Distillation Framework and a Feature Compensation Module to learn domain-invariant representations from multi-source data, …

V2X-ViT is build upon OpenCOOD, which is the first Open Cooperative Detection framework for autonomous driving.

May 7, 2024 · The pipeline efficiently processes data from 4 cameras and 4 corresponding LiDARs, inferencing the 3D bboxes with a new model which combines the BEVFusion model …

To accelerate computer vision research and inno-vation for Vehicle-Infrastructure Cooperative Autonomous Driving (VICAD), we release DAIR-V2X Dataset, which is the first large-scale, …

In this paper, we propose DI-V2X, that aims to learn Domain-Invariant representations through a new distillation framework to mitigate the domain discrepancy in the context of V2X 3D object …

Apr 12, 2022 · The Vehicle-Infrastructure Cooperative 3D Object Detection problem (VIC3D) is introduced, formulating the problem of collaboratively locating and identifying 3D objects using …

Nov 13, 2024 · V2X-R contains 12,079 scenarios with 37,727 frames of LiDAR and 4D radar point clouds, 150,908 images, and 170,859 annotated 3D vehicle bounding boxes. Subsequently, …