5 code implementations • 13 Nov 2024 • Yingqi Gao, Yifu Liu, Xiaoxia Li, Xiaorong Shi, Yin Zhu, Yiming Wang, Shiqi Li, Wei Li, Yuntao Hong, Zhiling Luo, Jinyang Gao, Liyu Mou, Yu Li
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
no code implementations • 24 Sep 2024 • Naiwen Hu, Haozhe Cheng, Yifan Xie, Shiqi Li, Jihua Zhu
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)
no code implementations • 15 Sep 2024 • Shiqi Li, Jihua Zhu, Yifan Xie, Naiwen Hu, Mingchen Zhu, Zhongyu Li, Di Wang
Our method synthesizes the merit of both optimization-based and learning-based methods.
no code implementations • 10 Jul 2024 • Shiqi Li, Jihua Zhu, Yifan Xie, Mingchen Zhu
In this paper, we propose an incremental multiview point cloud registration method that progressively registers all scans to a growing meta-shape.
1 code implementation • 9 Jan 2024 • Yifan Xie, Boyu Wang, Shiqi Li, Jihua Zhu
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.
1 code implementation • 2 Nov 2023 • Yifan Xie, Jihua Zhu, Shiqi Li, Pengcheng Shi
Specifically, we first incorporate the projected images from the point clouds and fuse the cross-modal features using the attention mechanism.
no code implementations • 18 Oct 2023 • Shiqi Li, Jihua Zhu, Yifan Xie
Point cloud registration plays a crucial role in various computer vision tasks, and usually demands the resolution of partial overlap registration in practice.
no code implementations • 21 May 2022 • Shiqi Li, Xiang Xiang
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.
no code implementations • WS 2018 • Chao Bei, Hao Zong, Yiming Wang, Baoyong Fan, Shiqi Li, Conghu Yuan
The submitted system focus on data clearing and techniques to build a competitive model for this task.