1 citations · 3 across the 13 of their papers we have counts for
14 papers
Towards Scaling Marine Perception with Synthetic Data
Haoyu Ma, Onur Bagoren, Anja Sheppard +6
Scalable machine learning in challenging underwater environments is strongly limited by the lack of labeled real-world training data. This data is often expensive and laborious to…
CRISP: A Spatiotemporal Camera-Radar Backbone for Driving via Forecasting-Based World-Model Pretraining
Jingyu Song, Yi Liu, Katherine A. Skinner
Camera-radar (CR) fusion is a practical sensing configuration for autonomous driving, but existing models are typically trained with task-specific supervision, limiting reusable re…
CHyLL: Learning Continuous Neural Representations of Hybrid Systems
Sangli Teng, Hang Liu, Jingyu Song +1
Learning the flows of hybrid systems that have both continuous and discrete time dynamics is challenging. The existing method learns the dynamics in each discrete mode, which suffe…
FishDetector-R1: Unified MLLM-Based Framework with Reinforcement Fine-Tuning for Weakly Supervised Fish Detection, Segmentation, and Counting
Yi Liu, Jingyu Song, Vedanth Kallakuri +1
Analyzing underwater fish imagery is critical for ecological monitoring but remains difficult due to visual degradation and costly annotations. We introduce FishDetector-R1, a unif…
Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorer
Zhenxin Li, Nadine Chang, Wenhao Yao +9
Human demonstrations are widely considered the cornerstone of end-to-end (E2E) autonomous driving despite human demonstration's scarcity for long-tail and safety-critical scenarios…
DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Models
Jingyu Song, Zhenxin Li, Shiyi Lan +6
Benchmarking autonomous driving planners to align with human judgment remains a critical challenge, as state-of-the-art metrics like the Extended Predictive Driver Model Score (EPD…
OceanSim: A GPU-Accelerated Underwater Robot Perception Simulation Framework
Jingyu Song, Haoyu Ma, Onur Bagoren +3
Underwater simulators offer support for building robust underwater perception solutions. Significant work has recently been done to develop new simulators and to advance the perfor…
MemFusionMap: Working Memory Fusion for Online Vectorized HD Map Construction
Jingyu Song, Xudong Chen, Liupei Lu +2
High-definition (HD) maps provide environmental information for autonomous driving systems and are essential for safe planning. While existing methods with single-frame input achie…
TURTLMap: Real-time Localization and Dense Mapping of Low-texture Underwater Environments with a Low-cost Unmanned Underwater Vehicle
Jingyu Song, Onur Bagoren, Razan Andigani +2
Significant work has been done on advancing localization and mapping in underwater environments. Still, state-of-the-art methods are challenged by low-texture environments, which i…
CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation
Lingjun Zhao, Jingyu Song, Katherine A. Skinner
In the field of 3D object detection for autonomous driving, LiDAR-Camera (LC) fusion is the top-performing sensor configuration. Still, LiDAR is relatively high cost, which hinders…
LiRaFusion: Deep Adaptive LiDAR-Radar Fusion for 3D Object Detection
Jingyu Song, Lingjun Zhao, Katherine A. Skinner
We propose LiRaFusion to tackle LiDAR-radar fusion for 3D object detection to fill the performance gap of existing LiDAR-radar detectors. To improve the feature extraction capabili…
Uncertainty-Aware Acoustic Localization and Mapping for Underwater Robots
Jingyu Song, Onur Bagoren, Katherine A. Skinner
For underwater vehicles, robotic applications have the added difficulty of operating in highly unstructured and dynamic environments. Environmental effects impact not only the dyna…
Convolutional Bayesian Kernel Inference for 3D Semantic Mapping
Joey Wilson, Yuewei Fu, Arthur Zhang +5
Robotic perception is currently at a cross-roads between modern methods, which operate in an efficient latent space, and classical methods, which are mathematically founded and pro…
MotionSC: Data Set and Network for Real-Time Semantic Mapping in Dynamic Environments
Joey Wilson, Jingyu Song, Yuewei Fu +5
This work addresses a gap in semantic scene completion (SSC) data by creating a novel outdoor data set with accurate and complete dynamic scenes. Our data set is formed from random…