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University of Michigan
- Ann Arbor
- https://song-jingyu.github.io/
- in/jingyu-song-93763a132
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[IROS 2025] MarineGym: A High-Performance Reinforcement Learning Platform for Underwater Robotics; Contact Email: zjuoyh@163.com
This QGIS plugin finds shipwrecks from multibeam sonar data.
EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL
A simple visual test-time scaling method for GUI agent grounding
(ICCV2025) End-to-End Driving with Online Trajectory Evaluation via BEV World Model
[ICLR 2025] Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception
[ICCV 2025] Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives
[CVPR2025] The code for "Uncertainty-Instructed Structure Injection for Generalizable HD Map Construction."
[RA-L 2025] Distributional Reinforcement Learning Based Integrated Decision Making and Control for Autonomous Surface Vehicles
[IROS 2025] OceanSim: A GPU-Accelerated Underwater Robot Perception Simulation Framework
[WACV 2025] MemFusionMap: Working Memory Fusion for Online Vectorized HD Map Construction
[CVPR 2025 Highlight] Video Depth Anything: Consistent Depth Estimation for Super-Long Videos
New repo collection for NVIDIA Cosmos: https://github.com/nvidia-cosmos
[CVPR'25] LiMoE: Mixture of LiDAR Representation Learners from Automotive Scenes
[Lumina具身智能社区] 具身智能技术指南 Embodied-AI-Guide
The official repository of "MarineInst: A Foundation Model for Marine Image Analysis with Instance Visual Description". [ECCV Oral 2024.]
Dead Reckoning In Field Time: Symmetry-Preserving State Estimation Library for Various Robotic Platforms
Extension and update of M2DGR: a novel Multi-modal and Multi-scenario SLAM Dataset for Ground Robots (ICRA2022 & ICRA2024)
A curated list of radar datasets, detection, tracking and fusion
[CVPR 2025 (Oral)] Open implementation of "RandAR"
[CVPR 2024 Highlight] Visual Point Cloud Forecasting
[ECCV 2024] The official code for "Dolphins: Multimodal Language Model for Driving“


