5 papers
STAR-VLM: Spatiotemporal Grounding Vision-Language Models for Motion and Velocity Estimation via Automotive Radar Supervision
Pou-Chun Kung, Aryaman Rao, Utkrisht Sahai +4
Vision-language models (VLMs) are emerging as a key component of embodied intelligence, with growing applications in auto-labeling and end-to-end autonomous driving. However, exist…
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…
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…
CoST: Efficient Collaborative Perception From Unified Spatiotemporal Perspective
Zongheng Tang, Yi Liu, Yifan Sun +4
Collaborative perception shares information among different agents and helps solving problems that individual agents may face, e.g., occlusions and small sensing range. Prior metho…
CycleVAR: Repurposing Autoregressive Model for Unsupervised One-Step Image Translation
Yi Liu, Shengqian Li, Zuzeng Lin +2
The current conditional autoregressive image generation methods have shown promising results, yet their potential remains largely unexplored in the practical unsupervised image tra…