1 citations · 5 across the 12 of their papers we have counts for
13 papers
PrecipJEPA: JEPA-Regularized Future-State Prediction with Motion-Source Rendering for Precipitation Nowcasting
Yufeng Zhu, Dan Niu, Qiliang Wu +4
Long-term precipitation nowcasting requires modeling radar-echo evolution while preserving localized high-intensity structures. Recent radar-specific studies motivate location-awar…
WaveOp-LiteFM: Lightweight Neural-Operator Flow Matching for Satellite-to-Radar Precipitation Retrieval
Chunlei Shi, Yecheng Zhang, Yufeng Zhu +4
Satellite-to-radar (S2R) retrieval refers to estimating ground-based radar precipitation from geostationary satellite observations, enabling precipitation monitoring in regions wit…
GigaBrain-0.7: Scaling Embodied Foundation Models to Emergent Capabilities with a Three-System Architecture
GigaBrain Team, Angen Ye, Axiang Sun +56
Vision-language-action (VLA) models have become a dominant paradigm for generalist embodied agents, demonstrating strong complex and long-horizon task completion in structured sett…
MambaRain: Multi-Scale Mamba-Attention Framework for 0-3 Hour Precipitation Nowcasting
Chunlei Shi, Cui Wu, Xiang Xu +10
Accurate precipitation nowcasting over extended horizons (0-3 hours) is essential for disaster mitigation and operational decision-making, yet remains a critical challenge in the f…
VMU-Diff: A Coarse-to-fine Multi-source Data Fusion Framework for Precipitation Nowcasting
Chunlei Shi, Hao Li, Yufeng Zhu +6
Precipitation nowcasting is a vital spatio-temporal prediction task for meteorological applications but faces challenges due to the chaotic property of precipitation systems. Exist…
PixelFlowCast: Latent-Free Precipitation Nowcasting via Pixel Mean Flows
Yufeng Zhu, Chunlei Shi, Yongchao Feng +1
Precipitation nowcasting aims to forecast short-term radar echo sequences for extreme weather warning, where both prediction fidelity and inference efficiency are critical for real…
Uni-MDTrack: Learning Decoupled Memory and Dynamic States for Parameter-Efficient Visual Tracking in All Modality
Wenrui Cai, Zhenyi Lu, Yuzhe Li +4
With the advent of Transformer-based one-stream trackers that possess strong capability in inter-frame relation modeling, recent research has increasingly focused on how to introdu…
WaveC2R: Wavelet-Driven Coarse-to-Refined Hierarchical Learning for Radar Retrieval
Chunlei Shi, Han Xu, Yinghao Li +4
Satellite-based radar retrieval methods are widely employed to fill coverage gaps in ground-based radar systems, especially in remote areas affected by terrain blockage and limited…
Vision-Language Model for Object Detection and Segmentation: A Review and Evaluation
Yongchao Feng, Yajie Liu, Shuai Yang +13
Vision-Language Model (VLM) have gained widespread adoption in Open-Vocabulary (OV) object detection and segmentation tasks. Despite they have shown promise on OV-related tasks, th…
OpenRSD: Towards Open-prompts for Object Detection in Remote Sensing Images
Ziyue Huang, Yongchao Feng, Shuai Yang +3
Remote sensing object detection has made significant progress, but most studies still focus on closed-set detection, limiting generalization across diverse datasets. Open-vocabular…
PACF: Prototype Augmented Compact Features for Improving Domain Adaptive Object Detection
Chenguang Liu, Yongchao Feng, Yanan Zhang +2
In recent years, there has been significant advancement in object detection. However, applying off-the-shelf detectors to a new domain leads to significant performance drop, caused…
MutDet: Mutually Optimizing Pre-training for Remote Sensing Object Detection
Ziyue Huang, Yongchao Feng, Qingjie Liu +1
Detection pre-training methods for the DETR series detector have been extensively studied in natural scenes, e.g., DETReg. However, the detection pre-training remains unexplored in…
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection
Yongchao Feng, Shiwei Li, Yingjie Gao +4
Though feature-alignment based Domain Adaptive Object Detection (DAOD) methods have achieved remarkable progress, they ignore the source bias issue, i.e., the detector tends to acq…