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20212023
most citedWT-MVSNet: Window-based Transformers for Multi-view Stereo

17 citations · 41 across the 8 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.CV2022★ 6 cited

Rethinking Dimensionality Reduction in Grid-based 3D Object Detection

Dihe Huang, Ying Chen, Yikang Ding +7

Bird's eye view (BEV) is widely adopted by most of the current point cloud detectors due to the applicability of well-explored 2D detection techniques. However, existing methods ob…

cs.CV2022

Sobolev Training for Implicit Neural Representations with Approximated Image Derivatives

Wentao Yuan, Qingtian Zhu, Xiangyue Liu +3

Recently, Implicit Neural Representations (INRs) parameterized by neural networks have emerged as a powerful and promising tool to represent different kinds of signals due to its c…

cs.CV2022★ 1 cited

KD-MVS: Knowledge Distillation Based Self-supervised Learning for Multi-view Stereo

Yikang Ding, Qingtian Zhu, Xiangyue Liu +3

Supervised multi-view stereo (MVS) methods have achieved remarkable progress in terms of reconstruction quality, but suffer from the challenge of collecting large-scale ground-trut…

cs.CV2022★ 3 cited

Adaptive Assignment for Geometry Aware Local Feature Matching

Dihe Huang, Ying Chen, Shang Xu +5

The detector-free feature matching approaches are currently attracting great attention thanks to their excellent performance. However, these methods still struggle at large-scale a…

cs.CV2022

Enhancing Multi-view Stereo with Contrastive Matching and Weighted Focal Loss

Yikang Ding, Zhenyang Li, Dihe Huang +2

Learning-based multi-view stereo (MVS) methods have made impressive progress and surpassed traditional methods in recent years. However, their accuracy and completeness are still s…

cs.CV2022★ 17 cited

WT-MVSNet: Window-based Transformers for Multi-view Stereo

Jinli Liao, Yikang Ding, Yoli Shavit +5

Recently, Transformers were shown to enhance the performance of multi-view stereo by enabling long-range feature interaction. In this work, we propose Window-based Transformers (WT…