In the realm of modern autonomous driving, the perception system is indispensable for
accurately assessing the state of the surrounding environment, thereby enabling informed …

In this paper, we propose a long-sequence modeling framework, named StreamPETR, for
multi-view 3D object detection. Built upon the sparse query design in the PETR series, we …

Abstract View Transformation Module (VTM), where transformations happen between multi-
view image features and Bird-Eye-View (BEV) representation, is a crucial step in camera …

In recent years, the realm of deep learning has witnessed significant advancements,
particularly in object detection algorithms. However, the unique challenges posed by remote …

High-definition (HD) vectorized map is essential for autonomous driving, providing detailed
and precise environmental information for advanced perception and planning. However …

Monocular 3D detectors achieve remarkable performance on cars and smaller objects.
However their performance drops on larger objects leading to fatal accidents. Some attribute …

Over recent years, the Vehicle-Road-Cloud Integration System (VRCIS) and Intelligent and
Connected Vehicles (ICVs) have gained significant attention in the realm of autonomous …

In autonomous driving, 3D occupancy prediction outputs voxel-wise status and semantic
labels for more comprehensive understandings of 3D scenes compared with traditional …

Multi-view 3D object detection is becoming popular in autonomous driving due to its high
effectiveness and low cost. Most of the current state-of-the-art detectors follow the query …