… detection methods. First, we present the broad background of multi-modal 3D object detection
and … and research trends for realizing the full potential of multi-modal 3D object detection. …

… for the long-range object detection. We develop a family of multi-modal 3D detection models …
compatible with many existing voxel-based 3D detection methods. DeepFusion serves as a …

… in developing a deep multi-modal transformer backbone to capture richer global contexts
for 3D object detection. To this end, we propose a novel multi-modal transformer network, …

… properties, and the corresponding object detection algorithms. Next, we … multi-modal 3D
object detection algorithms. Then we present a review of multi-modal fusion based 3D detection …

… Recent progress on multi-modal 3D object detection has … misalignment between these two
multi-modal features. Moreover, such … In this paper, we propose a novel Object-centric Fusion (…

… accuracy and robustness of 3D object detectors, especially for sparse scenes. In this paper,
we design a novel multi-modal fusion framework for 3D object detection named EPNet++, …

… 3D object detection with multi-modal input of point cloud data and RGB image, this paper
proposed a deep multi-scale multi-modal … the performance of 3D object detection. The results of …

… 2, we propose a deep learning framework to deal with multi-modal-based 3D object
detection by 2D-guided PAG-Net and multi-layer fusion. Inspired by [15], [27], [45], we take BEV …

… Multi-modal 3D object detection has been an active research topic in autonomous driving.
Nevertheless, it is non-trivial to explore the cross-modal feature fusion between sparse …

… issues to deploy detectors in crowded scenes. … multi-modal based object detector in an
automated driving system with early fusion on 3D object detection utilizing both Light Detection …