201 citations · 555 across the 21 of their papers we have counts for
21 papers
Pseudogap and Non-Fermi-liquid criticality in double Kondo model for bilayer nickelates
Jing-Yu Zhao, Ya-Hui Zhang
Motivated by recent experimental progress on high-temperature superconductivity in bilayer nickelates, we investigate the phase diagram of the normal state in a bilayer Kondo latti…
Affine-based Deformable Attention and Selective Fusion for Semi-dense Matching
Hongkai Chen, Zixin Luo, Yurun Tian +8
Identifying robust and accurate correspondences across images is a fundamental problem in computer vision that enables various downstream tasks. Recent semi-dense matching methods…
ASpanFormer: Detector-Free Image Matching with Adaptive Span Transformer
Hongkai Chen, Zixin Luo, Lei Zhou +6
Generating robust and reliable correspondences across images is a fundamental task for a diversity of applications. To capture context at both global and local granularity, we prop…
Learning to Match Features with Seeded Graph Matching Network
Hongkai Chen, Zixin Luo, Jiahui Zhang +5
Matching local features across images is a fundamental problem in computer vision. Targeting towards high accuracy and efficiency, we propose Seeded Graph Matching Network, a graph…
PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency
Xuyang Bai, Zixin Luo, Lei Zhou +5
Removing outlier correspondences is one of the critical steps for successful feature-based point cloud registration. Despite the increasing popularity of introducing deep learning…
Visibility-aware Multi-view Stereo Network
Jingyang Zhang, Yao Yao, Shiwei Li +2
Learning-based multi-view stereo (MVS) methods have demonstrated promising results. However, very few existing networks explicitly take the pixel-wise visibility into consideration…
Learning Stereo Matchability in Disparity Regression Networks
Jingyang Zhang, Yao Yao, Zixin Luo +4
Learning-based stereo matching has recently achieved promising results, yet still suffers difficulties in establishing reliable matches in weakly matchable regions that are texture…
Stochastic Bundle Adjustment for Efficient and Scalable 3D Reconstruction
Lei Zhou, Zixin Luo, Mingmin Zhen +5
Current bundle adjustment solvers such as the Levenberg-Marquardt (LM) algorithm are limited by the bottleneck in solving the Reduced Camera System (RCS) whose dimension is proport…
ASLFeat: Learning Local Features of Accurate Shape and Localization
Zixin Luo, Lei Zhou, Xuyang Bai +6
This work focuses on mitigating two limitations in the joint learning of local feature detectors and descriptors. First, the ability to estimate the local shape (scale, orientation…
KFNet: Learning Temporal Camera Relocalization using Kalman Filtering
Lei Zhou, Zixin Luo, Tianwei Shen +5
Temporal camera relocalization estimates the pose with respect to each video frame in sequence, as opposed to one-shot relocalization which focuses on a still image. Even though th…
D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
Xuyang Bai, Zixin Luo, Lei Zhou +3
A successful point cloud registration often lies on robust establishment of sparse matches through discriminative 3D local features. Despite the fast evolution of learning-based 3D…
BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networks
Yao Yao, Zixin Luo, Shiwei Li +5
While deep learning has recently achieved great success on multi-view stereo (MVS), limited training data makes the trained model hard to be generalized to unseen scenarios. Compar…
Self-Supervised Learning of Depth and Motion Under Photometric Inconsistency
Tianwei Shen, Lei Zhou, Zixin Luo +5
The self-supervised learning of depth and pose from monocular sequences provides an attractive solution by using the photometric consistency of nearby frames as it depends much les…
Learning Two-View Correspondences and Geometry Using Order-Aware Network
Jiahui Zhang, Dawei Sun, Zixin Luo +6
Establishing correspondences between two images requires both local and global spatial context. Given putative correspondences of feature points in two views, in this paper, we pro…
ContextDesc: Local Descriptor Augmentation with Cross-Modality Context
Zixin Luo, Tianwei Shen, Lei Zhou +5
Most existing studies on learning local features focus on the patch-based descriptions of individual keypoints, whereas neglecting the spatial relations established from their keyp…
Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference
Yao Yao, Zixin Luo, Shiwei Li +3
Deep learning has recently demonstrated its excellent performance for multi-view stereo (MVS). However, one major limitation of current learned MVS approaches is the scalability: t…
Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation
Tianwei Shen, Zixin Luo, Lei Zhou +4
Accurate relative pose is one of the key components in visual odometry (VO) and simultaneous localization and mapping (SLAM). Recently, the self-supervised learning framework that…
Matchable Image Retrieval by Learning from Surface Reconstruction
Tianwei Shen, Zixin Luo, Lei Zhou +4
Convolutional Neural Networks (CNNs) have achieved superior performance on object image retrieval, while Bag-of-Words (BoW) models with handcrafted local features still dominate th…
GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints
Zixin Luo, Tianwei Shen, Lei Zhou +5
Learned local descriptors based on Convolutional Neural Networks (CNNs) have achieved significant improvements on patch-based benchmarks, whereas not having demonstrated strong gen…
Learning and Matching Multi-View Descriptors for Registration of Point Clouds
Lei Zhou, Siyu Zhu, Zixin Luo +5
Critical to the registration of point clouds is the establishment of a set of accurate correspondences between points in 3D space. The correspondence problem is generally addressed…
MVSNet: Depth Inference for Unstructured Multi-view Stereo
Yao Yao, Zixin Luo, Shiwei Li +2
We present an end-to-end deep learning architecture for depth map inference from multi-view images. In the network, we first extract deep visual image features, and then build the…