리뷰6 [Paper Review] MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization 논문 : MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization URL : arxiv.org/abs/1811.10247 MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization Detecting and localizing objects in the real 3D space, which plays a crucial role in scene understanding, is particularly challenging given only a single RGB image due to the geometric information loss duri.. 2021. 5. 1. [Paper Review] GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving 논문 : GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving URL : arxiv.org/abs/1903.10955 GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving We present an efficient 3D object detection framework based on a single RGB image in the scenario of autonomous driving. Our efforts are put on extracting the underlying 3D information in a 2D image and determining the.. 2021. 5. 1. [Paper Review] Disentangling Monocular 3D Object Detection (MonoDis) 논문 : Disentangling Monocular 3D Object Detection (MonoDis) URL : arxiv.org/abs/1905.12365 Disentangling Monocular 3D Object Detection In this paper we propose an approach for monocular 3D object detection from a single RGB image, which leverages a novel disentangling transformation for 2D and 3D detection losses and a novel, self-supervised confidence score for 3D bounding boxes. Our pro arxiv.o.. 2021. 5. 1. [Paper Review] Pyramid Stereo Matching Network(PSMNet) 논문 : Pyramid Stereo Matching Network (PSMNet) URL : arxiv.org/abs/1803.08669 Pyramid Stereo Matching Network Recent work has shown that depth estimation from a stereo pair of images can be formulated as a supervised learning task to be resolved with convolutional neural networks (CNNs). However, current architectures rely on patch-based Siamese networks, lacking arxiv.org 저자 : Jia-Ren Chang, Yon.. 2021. 5. 1. 이전 1 2 다음 반응형
