Search Results for author: Maosheng Ye

Found 8 papers, 0 papers with code

PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving

no code implementations14 Nov 2023 Zhili Chen, Maosheng Ye, Shuangjie Xu, Tongyi Cao, Qifeng Chen

Unlike existing end-to-end autonomous driving frameworks, PPAD models the interactions among ego, agents, and the dynamic environment in an autoregressive manner by interleaving the Prediction and Planning processes at every timestep, instead of a single sequential process of prediction followed by planning.

Autonomous Driving Motion Planning

Bootstrap Motion Forecasting With Self-Consistent Constraints

no code implementations ICCV 2023 Maosheng Ye, Jiamiao Xu, Xunnong Xu, Tengfei Wang, Tongyi Cao, Qifeng Chen

Also, to model the multi-modality in motion forecasting, we design a novel self-ensembling scheme to obtain accurate teacher targets to enforce the self-constraints with multi-modality supervision.

Motion Forecasting

Sparse Cross-scale Attention Network for Efficient LiDAR Panoptic Segmentation

no code implementations16 Jan 2022 Shuangjie Xu, Rui Wan, Maosheng Ye, Xiaoyi Zou, Tongyi Cao

Two major challenges of 3D LiDAR Panoptic Segmentation (PS) are that point clouds of an object are surface-aggregated and thus hard to model the long-range dependency especially for large instances, and that objects are too close to separate each other.

Panoptic Segmentation

DRINet++: Efficient Voxel-as-point Point Cloud Segmentation

no code implementations16 Nov 2021 Maosheng Ye, Rui Wan, Shuangjie Xu, Tongyi Cao, Qifeng Chen

The Sparse Feature Encoder extracts the local context information for each point, and the Sparse Geometry Feature Enhancement enhances the geometric properties of a sparse point cloud via multi-scale sparse projection and attentive multi-scale fusion.

Point Cloud Segmentation Segmentation +1

TPCN: Temporal Point Cloud Networks for Motion Forecasting

no code implementations CVPR 2021 Maosheng Ye, Tongyi Cao, Qifeng Chen

We propose the Temporal Point Cloud Networks (TPCN), a novel and flexible framework with joint spatial and temporal learning for trajectory prediction.

Motion Forecasting Trajectory Prediction

HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection

no code implementations CVPR 2020 Maosheng Ye, Shuangjie Xu, Tongyi Cao

We present a Hybrid Voxel network that solves this problem by fusing voxel feature encoder (VFE) of different scales at point-wise level and project into multiple pseudo-image feature maps.

3D Object Detection Autonomous Driving +1

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