17 citations · 41 across the 8 of their papers we have counts for
8 papers
LayerDiffusion: Layered Controlled Image Editing with Diffusion Models
Pengzhi Li, QInxuan Huang, Yikang Ding +1
Text-guided image editing has recently experienced rapid development. However, simultaneously performing multiple editing actions on a single image, such as background replacement…
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…
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…
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…
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…
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…
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…
TransMVSNet: Global Context-aware Multi-view Stereo Network with Transformers
Yikang Ding, Wentao Yuan, Qingtian Zhu +4
In this paper, we present TransMVSNet, based on our exploration of feature matching in multi-view stereo (MVS). We analogize MVS back to its nature of a feature matching task and t…