9 citations · 19 across the 8 of their papers we have counts for
9 papers
Rethinking 3D Shape Generation: Diffusion over Superquadrics
Zhiyang Liu, Wanze Li, Yuwei Wu +4
Diffusion models have advanced 3D shape generation, yet most methods still denoise in high-cardinality spaces (e.g., voxel/SDF grids, meshes, or point clouds), which is computation…
RMGS-SLAM: Real-time Multi-sensor Gaussian Splatting SLAM
Dongen Li, Yi Liu, Junqi Liu +8
Achieving real-time Simultaneous Localization and Mapping (SLAM) based on 3D Gaussian splatting (3DGS) in large-scale real-world environments remains challenging, as existing metho…
PIE: Perception and Interaction Enhanced End-to-End Motion Planning for Autonomous Driving
Chengran Yuan, Zijian Lu, Zhanqi Zhang +8
End-to-end motion planning is promising for simplifying complex autonomous driving pipelines. However, challenges such as scene understanding and effective prediction for decision-…
AGI-Elo: How Far Are We From Mastering A Task?
Shuo Sun, Yimin Zhao, Christina Dao Wen Lee +8
As the field progresses toward Artificial General Intelligence (AGI), there is a pressing need for more comprehensive and insightful evaluation frameworks that go beyond aggregate…
RMP-YOLO: A Robust Motion Predictor for Partially Observable Scenarios even if You Only Look Once
Jiawei Sun, Jiahui Li, Tingchen Liu +6
We introduce RMP-YOLO, a unified framework designed to provide robust motion predictions even with incomplete input data. Our key insight stems from the observation that complete a…
DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba
Chengran Yuan, Zhanqi Zhang, Jiawei Sun +8
Motion planning is a challenging task to generate safe and feasible trajectories in highly dynamic and complex environments, forming a core capability for autonomous vehicles. In t…
ADM: Accelerated Diffusion Model via Estimated Priors for Robust Motion Prediction under Uncertainties
Jiahui Li, Tianle Shen, Zekai Gu +5
Motion prediction is a challenging problem in autonomous driving as it demands the system to comprehend stochastic dynamics and the multi-modal nature of real-world agent interacti…
ControlMTR: Control-Guided Motion Transformer with Scene-Compliant Intention Points for Feasible Motion Prediction
Jiawei Sun, Chengran Yuan, Shuo Sun +7
The ability to accurately predict feasible multimodal future trajectories of surrounding traffic participants is crucial for behavior planning in autonomous vehicles. The Motion Tr…
Multi-Scale Feature Aggregation by Cross-Scale Pixel-to-Region Relation Operation for Semantic Segmentation
Yechao Bai, Ziyuan Huang, Lyuyu Shen +3
Exploiting multi-scale features has shown great potential in tackling semantic segmentation problems. The aggregation is commonly done with sum or concatenation (concat) followed b…