Learning Manipulation by Predicting Interaction

1 code implementation • 1 Jun 2024 • Jia Zeng, Qingwen Bu, Bangjun Wang, Wenke Xia, Li Chen, Hao Dong, Haoming Song, Dong Wang, Di Hu, Ping Luo, Heming Cui, Bin Zhao, Xuelong Li, Yu Qiao, Hongyang Li

To this end, we propose a general pre-training pipeline that learns Manipulation by Predicting the Interaction (MPI) and enhances the visual representation. Given a pair of keyframes representing the initial and final states, along with language instructions, our algorithm predicts the transition frame and detects the interaction object, respectively.

LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving

1 code implementation • 26 Dec 2023 • Tianyu Li, Peijin Jia, Bangjun Wang, Li Chen, Kun Jiang, Junchi Yan, Hongyang Li

A map, as crucial information for downstream applications of an autonomous driving system, is usually represented in lanelines or centerlines.

Autonomous Driving

OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mapping

1 code implementation • NeurIPS 2023 • Huijie Wang, Tianyu Li, Yang Li, Li Chen, Chonghao Sima, Zhenbo Liu, Bangjun Wang, Peijin Jia, Yuting Wang, Shengyin Jiang, Feng Wen, Hang Xu, Ping Luo, Junchi Yan, Wei zhang, Hongyang Li

Accurately depicting the complex traffic scene is a vital component for autonomous vehicles to execute correct judgments.

3D Lane Detection