Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …

Learning powerful representations in bird's-eye-view (BEV) for perception tasks is trending
and drawing extensive attention both from industry and academia. Conventional …

Multi-sensor fusion is essential for an accurate and reliable autonomous driving system.
Recent approaches are based on point-level fusion: augmenting the LiDAR point cloud with …

LiDAR and camera are two important sensors for 3D object detection in autonomous driving.
Despite the increasing popularity of sensor fusion in this field, the robustness against inferior …

Sensor fusion is an essential topic in many perception systems, such as autonomous driving
and robotics. Existing multi-modal 3D detection models usually involve customized designs …

Existing top-performance 3D object detectors typically rely on the multi-modal fusion
strategy. This design is however fundamentally restricted due to overlooking the modality …

Abstract Vision-language navigation (VLN), which entails an agent to navigate 3D
environments following human instructions, has shown great advances. However, current …

Point clouds and RGB images are two general perceptional sources in autonomous driving.
The former can provide accurate localization of objects, and the latter is denser and richer in …

Transformer, as an alternative to CNN, has been proven effective in many modalities (eg,
texts and images). For 3D point cloud transformers, existing efforts focus primarily on …

Despite the tremendous progress of Masked Autoencoders (MAE) in develo** vision tasks
such as image and video, exploring MAE in large-scale 3D point clouds remains …