Robustness-aware 3d object detection in autonomous driving: A review and outlook
In the realm of modern autonomous driving, the perception system is indispensable for
accurately assessing the state of the surrounding environment, thereby enabling informed …
accurately assessing the state of the surrounding environment, thereby enabling informed …
Unipad: A universal pre-training paradigm for autonomous driving
In the context of autonomous driving the significance of effective feature learning is widely
acknowledged. While conventional 3D self-supervised pre-training methods have shown …
acknowledged. While conventional 3D self-supervised pre-training methods have shown …
Detecting as labeling: Rethinking lidar-camera fusion in 3d object detection
J Huang, Y Ye, Z Liang, Y Shan, D Du - European Conference on …, 2024 - Springer
Abstract 3D object Detection with LiDAR-camera encounters overfitting in algorithm
development derived from violating some fundamental rules. We refer to the data annotation …
development derived from violating some fundamental rules. We refer to the data annotation …
Recent advances in multi-modal 3D scene understanding: A comprehensive survey and evaluation
Multi-modal 3D scene understanding has gained considerable attention due to its wide
applications in many areas, such as autonomous driving and human-computer interaction …
applications in many areas, such as autonomous driving and human-computer interaction …
Is-fusion: Instance-scene collaborative fusion for multimodal 3d object detection
Bird's eye view (BEV) representation has emerged as a dominant solution for describing 3D
space in autonomous driving scenarios. However objects in the BEV representation typically …
space in autonomous driving scenarios. However objects in the BEV representation typically …
Fully sparse fusion for 3d object detection
Currently prevalent multi-modal 3D detection methods rely on dense detectors that usually
use dense Bird's-Eye-View (BEV) feature maps. However, the cost of such BEV feature …
use dense Bird's-Eye-View (BEV) feature maps. However, the cost of such BEV feature …
Ppad: Iterative interactions of prediction and planning for end-to-end autonomous driving
We present a new interaction mechanism of prediction and planning for end-to-end
autonomous driving, called PPAD (Iterative Interaction of P rediction and P lanning A …
autonomous driving, called PPAD (Iterative Interaction of P rediction and P lanning A …
OccFusion: Multi-Sensor Fusion Framework for 3D Semantic Occupancy Prediction
A comprehensive understanding of 3D scenes is crucial in autonomous vehicles (AVs), and
recent models for 3D semantic occupancy prediction have successfully addressed the …
recent models for 3D semantic occupancy prediction have successfully addressed the …
Mv2dfusion: Leveraging modality-specific object semantics for multi-modal 3d detection
The rise of autonomous vehicles has significantly increased the demand for robust 3D object
detection systems. While cameras and LiDAR sensors each offer unique advantages …
detection systems. While cameras and LiDAR sensors each offer unique advantages …
Muvo: A multimodal generative world model for autonomous driving with geometric representations
Learning unsupervised world models for autonomous driving has the potential to improve
the reasoning capabilities of today's systems dramatically. However, most work neglects the …
the reasoning capabilities of today's systems dramatically. However, most work neglects the …