most citedTimeLDM: Latent Diffusion Model for Unconditional Time Series Generation

3 citations · 3 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

MAETrack: Unleashing the Potential of Pretrained Geometric Priors for 3D Single Object Tracking

Sifan Zhou, Qiwei Wang, Linyue Tan +3

Large-scale pre-training has transformed representation learning in 2D vision, yet its transferability to 3D single object tracking (SOT) remains insufficiently understood. Directl…

cs.CV2026

SAVTrack: Selective Vote Aggregation for Reliability-Aware Point Cloud Tracking

Sifan Zhou, Linyue Tan, Qiwei Wang +2

3D single object tracking (SOT) in LiDAR point clouds is essential for autonomous systems, but remains challenging under sparse and incomplete observations. In such cases, differen…

cs.CV2026

TFTrack: A Template-Free Framework for Efficient 3D Point Cloud Tracking

Zhaofeng Hu, Sifan Zhou, Jiahao Nie +3

LiDAR-based 3D Single Object Tracking (3D SOT) is critical for robotic perception and navigation and aims to localize dynamic objects across frames in sparse point clouds. Existing…

cs.CV2026

FocusTrack: One-Stage Focus-and-Suppress Framework for 3D Point Cloud Object Tracking

Sifan Zhou, Jiahao Nie, Ziyu Zhao +2

In 3D point cloud object tracking, the motion-centric methods have emerged as a promising avenue due to its superior performance in modeling inter-frame motion. However, existing t…

cs.LG2024

Sub-SA: Strengthen In-context Learning via Submodular Selective Annotation

Jian Qian, Miao Sun, Sifan Zhou +3

In-context learning (ICL) leverages in-context examples as prompts for the predictions of Large Language Models (LLMs). These prompts play a crucial role in achieving strong perfor…

cs.LG2024★ 3 cited

TimeLDM: Latent Diffusion Model for Unconditional Time Series Generation

Jian Qian, Bingyu Xie, Biao Wan +3

Time series generation is a crucial research topic in the area of decision-making systems, which can be particularly important in domains like autonomous driving, healthcare, and,…