6 accepted papers
Predicting pedestrian motion trajectories is critical for the path planning and motion control of autonomous vehicles. Recent diffusion-based models have shown promising results in capturing the inherent stochasticity of pedestrian behavior for trajectory prediction. However, the absence of explicit
LiDAR semantic segmentation is a key task in advanced autonomous driving systems. Projection-based methods exhibit real-time potential due to their efficiency, but suffer from inevitable 3D information loss and rely on time-consuming post-processing, limiting overall performance. To address this, we
We address the collaborative path planning problem for multi-agent systems with heterogeneous capabilities, subject to uncertainty and operating under complex task specifications. Conventional Probabilistic Signal Temporal Logic (PrSTL) frameworks exhibit significant limitations in describing multi-
We address the collaborative path planning problem for multi-agent systems with heterogeneous capabilities, subject to uncertainty and operating under complex task specifications. Conventional Probabilistic Signal Temporal Logic (PrSTL) frameworks exhibit significant limitations in describing multi-…
This position paper argues that building a reliable agentic web requires shifting from click-based browsing to typed actions supported by a standardized semantic layer. Today’s agents primarily operate over low-level primitives such as clicks, keystrokes, and DOM manipulation. This reliance leads to…
In the past decade, deep conditional generative models have revolutionized the generation of realistic images, extending their application from entertainment to scientific domains. Single-particle cryo-electron microscopy (cryo-EM) is crucial in resolving near-atomic resolution 3D structures of prot…