Learning Manipulation by Predicting Interaction

Jia Zeng$^\ast$, Qingwen Bu$^\ast$, Bangjun Wang$^\ast$, Wenke Xia$^\ast$, Li Chen, Hao Dong, H.Song, D.Wang, D.Hu, P.Luo, H.Cui, B.Zhao, X.Li, Y.Qiao, Hongyang Li

• We propose a representation learning framework towards robotic manipulation that learns Manipulation by Predicting Interaction (MPI).
• RSS 2024 | Project Page | Code

Closed-Loop Visuomotor Control with Generative Expectation for Robotic Manipulation

Qingwen Bu$^\ast$, Jia Zeng$^\ast$, Chen Li$^\ast$, Yanchao Yang, Guyue Zhou, Junchi Yan, Ping Luo, Heming Cui, D.Hu, Yi Ma, Hongyang Li

• We propose ​CLOVER, which employs a text-conditioned video diffusion model for generating visual plans as reference inputs, then leverages these sub-goals to guide the feedback-driven policy to generate actions with an error measurement strategy.
• NeurIPS 2024 | Code

Distilling Focal Knowledge From Imperfect Expert for 3D Object Detection

Jia Zeng, Li Chen, Hanming Deng, Lewei Lu, Junchi Yan, Yu Qiao, Hongyang Li

• We apply knowledge distillation to camera-only 3D object detection, investigate how to distill focal knowledge when confronted with an imperfect 3D object detector teacher.
• CVPR 2023

Geometric-aware Pretraining for Vision-centric 3D Object Detection

Linyan Huang, Huijie Wang, Jia Zeng, et al.

• We propose a geometric-aware pretraining method called GAPretrain, which distills geometric-rich information from LiDAR modality into camera-based 3D object detectors.
• arXiv

Delving Into the Devils of Bird’s-Eye-View Perception: A Review, Evaluation and Recipe

Hongyang Li$^\ast$, Chonghao Sima$^\ast$, Jifeng Dai$^\ast$, Wenhai Wang$^\ast$, Lewei Lu$^\ast$, Huijie Wang$^\ast$, Jia Zeng$^\ast$, Zhiqi Li$^\ast$, et al.

• we conduct a thorough review on Bird’s-Eye-View (BEV) perception in recent years and provide a practical recipe according to our analysis in BEV design pipeline.
• IEEE T-PAMI | Github

Open-sourced data ecosystem in autonomous driving: the present and future

Hongyang Li$^\ast$, Yang Li$^\ast$, Huijie Wang$^\ast$, Jia Zeng$^\ast$, Huilin Xu, et al.

• We undertakes an exhaustive analysis and discourse regarding the characteristics and data scales that future third-generation autonomous driving datasets should possess.
• SCIENTIA SINICA Informationis | arXiv