Search Results for author: Zeren Chen

Found 4 papers, 3 papers with code

RH20T-P: A Primitive-Level Robotic Dataset Towards Composable Generalization Agents

no code implementations28 Mar 2024 Zeren Chen, Zhelun Shi, Xiaoya Lu, Lehan He, Sucheng Qian, Hao Shu Fang, Zhenfei Yin, Wanli Ouyang, Jing Shao, Yu Qiao, Cewu Lu, Lu Sheng

The ultimate goals of robotic learning is to acquire a comprehensive and generalizable robotic system capable of performing both seen skills within the training distribution and unseen skills in novel environments.

Motion Planning

Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE

1 code implementation5 Nov 2023 Zeren Chen, Ziqin Wang, Zhen Wang, Huayang Liu, Zhenfei Yin, Si Liu, Lu Sheng, Wanli Ouyang, Yu Qiao, Jing Shao

While this phenomenon has been overlooked in previous work, we propose a novel and extensible framework, called Octavius, for comprehensive studies and experimentation on multimodal learning with Multimodal Large Language Models (MLLMs).

Zero-shot Generalization

Siamese DETR

1 code implementation CVPR 2023 Zeren Chen, Gengshi Huang, Wei Li, Jianing Teng, Kun Wang, Jing Shao, Chen Change Loy, Lu Sheng

In this work, we present Siamese DETR, a Siamese self-supervised pretraining approach for the Transformer architecture in DETR.

MULTI-VIEW LEARNING Representation Learning

Fast-BEV: A Fast and Strong Bird's-Eye View Perception Baseline

1 code implementation29 Jan 2023 Yangguang Li, Bin Huang, Zeren Chen, Yufeng Cui, Feng Liang, Mingzhu Shen, Fenggang Liu, Enze Xie, Lu Sheng, Wanli Ouyang, Jing Shao

Our Fast-BEV consists of five parts, We novelly propose (1) a lightweight deployment-friendly view transformation which fast transfers 2D image feature to 3D voxel space, (2) an multi-scale image encoder which leverages multi-scale information for better performance, (3) an efficient BEV encoder which is particularly designed to speed up on-vehicle inference.

Data Augmentation

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