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Cascade Network with Guided Loss and Hybrid Attention for Finding Good Correspondences
Finding good correspondences is a critical prerequisite in many feature ...
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DeepDT: Learning Geometry From Delaunay Triangulation for Surface Reconstruction
In this paper, a novel learning-based network, named DeepDT, is proposed...
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PVSNet: Pixelwise Visibility-Aware Multi-View Stereo Network
Recently, learning-based multi-view stereo methods have achieved promisi...
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Learning Inverse Depth Regression for Multi-View Stereo with Correlation Cost Volume
Deep learning has shown to be effective for depth inference in multi-vie...
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Planar Prior Assisted PatchMatch Multi-View Stereo
The completeness of 3D models is still a challenging problem in multi-vi...
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JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds
In this paper, we propose a novel joint instance and semantic segmentati...
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IoU-uniform R-CNN: Breaking Through the Limitations of RPN
Region Proposal Network (RPN) is the cornerstone of two-stage object det...
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TSRNet: Scalable 3D Surface Reconstruction Network for Point Clouds using Tangent Convolution
Existing learning-based surface reconstruction methods from point clouds...
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Localization-aware Channel Pruning for Object Detection
Channel pruning is one of the important methods for deep model compressi...
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GLA-Net: An Attention Network with Guided Loss for Mismatch Removal
Mismatch removal is a critical prerequisite in many feature-based tasks....
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Multi-Scale Geometric Consistency Guided Multi-View Stereo
In this paper, we propose an efficient multi-scale geometric consistency...
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GPU Accelerated Cascade Hashing Image Matching for Large Scale 3D Reconstruction
Image feature point matching is a key step in Structure from Motion(SFM)...
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Multi-View Stereo with Asymmetric Checkerboard Propagation and Multi-Hypothesis Joint View Selection
In computer vision domain, how to fast and accurately perform multiview ...
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Trilaminar Multiway Reconstruction Tree for Efficient Large Scale Structure from Motion
Accuracy and efficiency are two key problems in large scale incremental ...
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Convolutional Regression for Visual Tracking
Recently, discriminatively learned correlation filters (DCF) has drawn m...
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Once for All: a Two-flow Convolutional Neural Network for Visual Tracking
One of the main challenges of visual object tracking comes from the arbi...
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