201 citations · 599 across the 27 of their papers we have counts for
25 papers · 1 filter
Matrix3D: Large Photogrammetry Model All-in-One
Yuanxun Lu, Jingyang Zhang, Tian Fang +6
We present Matrix3D, a unified model that performs several photogrammetry subtasks, including pose estimation, depth prediction, and novel view synthesis using just the same model.…
Direct2.5: Diverse Text-to-3D Generation via Multi-view 2.5D Diffusion
Yuanxun Lu, Jingyang Zhang, Shiwei Li +6
Recent advances in generative AI have unveiled significant potential for the creation of 3D content. However, current methods either apply a pre-trained 2D diffusion model with the…
JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling
Jingyang Zhang, Shiwei Li, Yuanxun Lu +5
We introduce JointNet, a novel neural network architecture for modeling the joint distribution of images and an additional dense modality (e.g., depth maps). JointNet is extended f…
NeILF++: Inter-Reflectable Light Fields for Geometry and Material Estimation
Jingyang Zhang, Yao Yao, Shiwei Li +5
We present a novel differentiable rendering framework for joint geometry, material, and lighting estimation from multi-view images. In contrast to previous methods which assume a s…
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…
Critical Regularizations for Neural Surface Reconstruction in the Wild
Jingyang Zhang, Yao Yao, Shiwei Li +4
Neural implicit functions have recently shown promising results on surface reconstructions from multiple views. However, current methods still suffer from excessive time complexity…
NeILF: Neural Incident Light Field for Physically-based Material Estimation
Yao Yao, Jingyang Zhang, Jingbo Liu +5
We present a differentiable rendering framework for material and lighting estimation from multi-view images and a reconstructed geometry. In the framework, we represent scene light…
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…
Learning Discriminative Feature with CRF for Unsupervised Video Object Segmentation
Mingmin Zhen, Shiwei Li, Lei Zhou +4
In this paper, we introduce a novel network, called discriminative feature network (DFNet), to address the unsupervised video object segmentation task. To capture the inherent corr…
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…
Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency
Jiaxiang Shang, Tianwei Shen, Shiwei Li +4
Recent learning-based approaches, in which models are trained by single-view images have shown promising results for monocular 3D face reconstruction, but they suffer from the ill-…
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…
Joint Semantic Segmentation and Boundary Detection using Iterative Pyramid Contexts
Mingmin Zhen, Jinglu Wang, Lei Zhou +5
In this paper, we present a joint multi-task learning framework for semantic segmentation and boundary detection. The critical component in the framework is the iterative pyramid c…
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…
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…
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…