Jul 20, 2019 · In this work, we introduce a multi-resolution feature fusion convolution neural network using point cloud data for 3D object recognition.

In this work, we introduce a multi-resolution feature fusion convolution neural network using point cloud data for 3D object recognition. Experiments are ...

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We propose a multi-scale region of interest (ROI) feature fusion method from different resolution feature maps to better detect different size objects. •. We ...

This paper introduces an object detection approach based on multi-scale detection and scale linear regression. By initializing object queries on BEV feature ...

This study focuses on the problem of dense object counting. In dense scenes, variations in object scales and uneven distributions greatly hinder counting ...

Oct 8, 2024 · To tackle these issues, we propose in this paper a Dense Projection Fusion (DPFusion) approach. It consists of two new modules: dense depth map ...

In this work, we introduce a multi-resolution feature fusion convolution neural network using point cloud data for 3D object recognition. Experiments are ...

Highlights. •. We propose a multi-scale feature fusion method from different resolution feature maps for 3D object detection.

Oct 12, 2024 · This review paper focuses on the progress of deep learning-based methods for multi-view 3D object recognition.