A novel approach for 3D object recognition is proposed. The proposal relies on deep learning pre-trained models for image annotation.
Semi-supervised 3D Object Recognition through CNN Labeling
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Specifically, we take advantage of the spatial information in the 3D data to segment objects in the image and build an object classifier, and the classification ...
A novel approach for 3D object recognition is proposed. •. The proposal relies on deep learning pre-trained models for image annotation. •.
Semi-supervised 3D object recognition through CNN labeling ; Elsevier · Applied Soft Computing. 2018, 65: 603-613. doi:10.1016/j.asoc.2018.02.005.
Jul 11, 2024 · This paper presents a comprehensive review of 27 cutting-edge developments in SSOD methodologies, from Convolutional Neural Networks (CNNs) to Transformers.
In this paper, we propose to merge techniques using both 2D and 3D information to overcome these problems. Specifically, we take advantage of ...
Pseudo-Labeling (PL) is a critical approach in semi- supervised 3D object detection (SSOD). In PL, delicately selected pseudo-labels, generated by the ...
Missing: recognition | Show results with:recognition
Semi-Supervised 3D Object Recognition Through CNN Labeling by José Carlos Rangel, Jesus Martínez-Gómez, Cristina Romero-González, Ismael.
Sep 17, 2024 · Semi-supervised 3D object detection is a common strategy employed to circumvent the challenge of manually labeling large-scale autonomous ...
In this paper, we propose PatchTeacher, which fo- cuses on partial scene 3D object detection to provide high- quality pseudo labels for the student.
Missing: CNN | Show results with:CNN