Search Results for author:
Found 10 papers, 4 papers with code
Matching Distance and Geometric Distribution Aided Learning Multiview Point Cloud Registration
This paper concentrates on pose graph construction and motion synchronization within multiview registration.
A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL
On the other hand, we implement the ICL approach with an example selection method based on named entity recognition to prevent overemphasis on entities.
Ranked #1 on
Text-To-SQL
on SQL-Eval
3D-JEPA: A Joint Embedding Predictive Architecture for 3D Self-Supervised Representation Learning
Overall, 3D-JEPA predicts the representation of target blocks from a context block using the encoder and context-aware decoder architecture.
Ranked #3 on
Few-Shot 3D Point Cloud Classification
on ModelNet40 10-way (10-shot)
(using extra training data)
Multiple Rotation Averaging with Constrained Reweighting Deep Matrix Factorization
Our method synthesizes the merit of both optimization-based and learning-based methods.
Incremental Multiview Point Cloud Registration with Two-stage Candidate Retrieval
In this paper, we propose an incremental multiview point cloud registration method that progressively registers all scans to a growing meta-shape.
Iterative Feedback Network for Unsupervised Point Cloud Registration
In this paper, we propose a novel Iterative Feedback Network (IFNet) for unsupervised point cloud registration, in which the representation of low-level features is efficiently enriched by rerouting subsequent high-level features.
Cross-Modal Information-Guided Network using Contrastive Learning for Point Cloud Registration
Specifically, we first incorporate the projected images from the point clouds and fuse the cross-modal features using the attention mechanism.
DBDNet:Partial-to-Partial Point Cloud Registration with Dual Branches Decoupling
Point cloud registration plays a crucial role in various computer vision tasks, and usually demands the resolution of partial overlap registration in practice.
Lightweight Human Pose Estimation Using Heatmap-Weighting Loss
Recent research on human pose estimation exploits complex structures to improve performance on benchmark datasets, ignoring the resource overhead and inference speed when the model is actually deployed.
An Empirical Study of Machine Translation for the Shared Task of WMT18
The submitted system focus on data clearing and techniques to build a competitive model for this task.
