Haoran Geng | 耿浩然

I am a Ph.D. student at Berkeley AI Research (BAIR), advised by Prof. Jitendra Malik and Prof. Pieter Abbeel. I also work closely with Prof. Alexei (Alyosha) Efros, Prof. Leonidas J. Guibas and Prof. Yue Wang. Previously, I was a visiting scholar at Stanford University through UGVR program. I received my Bachelor's degree with honors from Turing Class, Peking University. During my undergraduate years, I was honored to be advised by Prof. Leonidas J. Guibas, Prof. He Wang, and Dr. Siyuan Huang. I am also grateful to have grown up and studied with my twin brother Yiran Geng, which has been a truly unique and special experience for me.

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News

  • [2024/09] 🎉 Three papers get accepted by CoRL 2024.
  • [2024/07] SAGE🌿 won the Best Paper Award at RSS 2024 SemRob Workshop
  • [2024/06] I won the Yunfan Award and was named as Rising Star at the World Artificial Intelligence Conference (top 15 early career Chinese AI researchers)! I am the only undergraduate student to win this award so far.
  • [2024/05] 🎉 SAGE gets accepted to RSS 2024.
  • [2024/03] I am honored to receive the Berkeley Fellowship Award and Stanford Graduate Fellowship Award.
  • [2023/12] Excited to announce Simulately🤖, a go-to toolkit for robotics researchers navigating diverse simulators!
  • [2023/12] I'm honored to be selected as one of the Person of the Year of Peking University.
  • [2023/10] I gave an Oral Presentation on UniDexGrasp++ at ICCV 2023.
  • [2023/10] 🎉 UniDexGrasp++ is selected as Best Paper Finalist at ICCV 2023.
  • [2023/08] 🎉 UniDexGrasp++ is selected as Oral Presentation at ICCV 2023.
  • [2023/07] 🎉 Two papers get accepted to ICCV 2023 with UniDexGrasp++ receiving final reviews of all strong accepts (the highest ratings).
  • [2023/07] 🎉 One paper gets accepted to Machine Learning Journal.
  • [2023/03] 🎉 GAPartNet is selected as a highlight at CVPR 2023 (Top 10% of accepted papers, top 2.5% of submissions).
  • [2023/02] 🎉 Three papers get accepted to CVPR 2023 with GAPartNet receiving final reviews of all accepts (the highest ratings).
  • [2023/01] 🎉 One paper gets accepted to ICRA 2023.

  • Research

    My research interest is broadly in Robotics and 3D Computer Vision, with particular interests in generalizable object perception, understanding and manipulation currently. My research objective is to build an intelligent agent with the robust and generalizable ability to perceive and interact with a complex real-world environment. Representative works are highlighted.

    RAM: Retrieval-Based Affordance Transfer for Generalizable Zero-Shot Robotic Manipulation
    Yuxuan Kuang*, Junjie Ye*, Haoran Geng*, Jiageng Mao, Congyue Deng, Leonidas Guibas, He Wang, Yue Wang
    (*equal contribution)
    Paper / Project / Code / Bibtex
    CoRL 2024, Oral Presentation

    RAM proposes a retrieve-and-transfer framework for zero-shot robotic manipulation, featuring generalizability across various objects, environments, and embodiments.


    Open6DOR: Benchmarking Open-instruction 6-DoF Object Rearrangement and A VLM-based Approach

    Yufei Ding*, Haoran Geng*, Chaoyi Xu, Xiaomeng Fang, Jiazhao Zhang, Songlin Wei, Qiyu Dai, Zhizheng Zhang, He Wang
    Project Page / Video
    IROS 2024, Oral Presentation

    We present Open6DOR, a challenging and comprehensive benchmark for open-instruction 6-DoF object rearrangement tasks. Following this, we propose a zero-shot and robust method, Open6DORGPT, which proves effective in demanding simulation environments and real-world scenarios.


    Simulately: Handy information and resources for physics simulators for robot learning research.

    Haoran Geng Yuyang Li, Yuzhe Qin, Ran Gong, Wensi Ai, Yuanpei Chen, Puhao Li, Junfeng Ni, Zhou Xian, Songlin Wei, Yang You, Yufei Ding, Jialiang Zhang
    Website / Github
    Open-source Project
    Selected into CMU 16-831

    Simulately is a project where we gather useful information of robotics & physics simulators for cutting-edge robot learning research.


    SAGE🌿: Bridging Semantic and Actionable Parts for Generalizable Articulated-Object Manipulation under Language Instructions

    Haoran Geng*, Songlin Wei*, Congyue Deng, Bokui Shen, He Wang, Leonidas Guibas
    ArXiv / Project Page / Video / Bibtex
    RSS 2024, Oral Presentation
    RSS 2024 @ SemRob, Best Paper Award

    We present SAGE, a framework bridging the understanding of semantic and actionable parts for generalizable manipulation of articulated objects using Large Language Models(LLMs) and Visual-Language Models(VLMs).

    Ag2Manip: Learning Novel Manipulation Skills with Agent-Agnostic Visual and Action Representations
    Puhao Li*, Tengyu Liu*, Yuyang Li, Muzhi Han, Haoran Geng, Shu Wang, Yixin Zhu, Song-Chun Zhu, Siyuan Huang
    Paper/ Code/ Project Page
    IROS 2024, Oral Presentation

    We introduce Ag2Manip, which enables various robotic manipulation tasks without any domain-specific demonstrations. Ag2Manip also supports robust imitation learning of manipulation skills in the real world.


    ShapeLLM: Universal 3D Object Understanding for Embodied Interaction

    Zekun Qi, Runpei Dong, Shaochen Zhang, Haoran Geng, Chunrui Han, Zheng Ge, He Wang, Li Yi, Kaisheng Ma
    ArXiv / Project Page / Bibtex
    ECCV 2024

    We present ShapeLLM, the first 3D Multimodal Large Language Model (LLM) designed for embodied interaction, exploring a universal 3D object understanding with 3D point clouds and languages.


    ManipLLM:Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation

    Xiaoqi Li, Mingxu Zhang, Yiran Geng, Haoran Geng, Yuxing Long, Yan Shen, Renrui Zhang, Jiaming Liu, Hao Dong
    ArXiv / Project Page / Bibtex
    CVPR 2024

    We present ManipLLM, introducing an innovative approach for robot manipulation that leverages the robust reasoning capabilities of Multimodal Large Language Models (MLLMs) to enhance the stability and generalization of manipulation.



    Make a Donut🍩: Language-guided Hierarchical EMD-Space Planning for Zero-shot Deformable Object Manipulation
    Yang You, Bokui Shen, Congyue Deng, Haoran Geng, He Wang, Leonidas Guibas
    ArXiv / Project Page / Bibtex
    Under Review

    In this work, we introduce a demonstration-free hierarchical planning approach capable of tackling intricate long-horizon tasks without necessitating any training



    UniDexGrasp++: Improving Dexterous Grasping Policy Learning via Geometry-aware Curriculum and Iterative Generalist-Specialist Learning
    Weikang Wan*, Haoran Geng*, Yun Liu, Zikang Shan, Yaodong Yang, Li Yi, He Wang
    (*equal contribution)
    ArXiv / Project Page / Code / Media(CFCS) / Bibtex
    ICCV 2023, Oral Presentation with all top ratings (strong accept)
    ICCV 2023, Best Paper Finalist

    We propose a novel, object-agnostic method for learning a universal policy for dexterous object grasping from realistic point cloud observations and proprioceptive information under a table-top setting.



    ARNOLD: A Benchmark for Language-Grounded Task Learning With Continuous States in Realistic 3D Scenes
    Ran Gong*, Jiangyong Huang*, Yizhou Zhao, Haoran Geng, Xiaofeng Gao, Qingyang Wu, Wensi Ai, Ziheng Zhou, Demetri Terzopoulos, Song-Chun Zhu, Baoxiong Jia, Siyuan Huang,
    ArXiv / Project Page / Code / Bibtex
    ICCV 2023
    CoRL 2022 @ LangRob, Spotlight Presentation

    We present ARNOLD, a benchmark that evaluates language-grounded task learning with continuous states in realistic 3D scenes.




    GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts

    Haoran Geng*, Helin Xu*, Chengyang Zhao*, Chao Xu, Li Yi, Siyuan Huang, He Wang
    ArXiv / Project Page / Code / Dataset / Poster / CVPR Page / Media(CFCS) / Bibtex
    CVPR 2023, Highlight (Top 2.5% of submissions) with all top ratings

    We propose to learn cross-category generalizable object perception and manipulation skills via Generalizable and Actionable Parts(GAPart), and present GAPartNet, a large-scale interactive dataset with rich part annotations.

    PartManip: Learning Cross-Category Generalizable Part Manipulation Policy from Point Cloud Observations
    Haoran Geng*, Ziming Li*, Yiran Geng, Jiayi Chen, Hao Dong, He Wang
    ArXiv / Project Page / Code / Dataset / Poster / CVPR Page / Bibtex
    CVPR 2023

    We introduce a large-scale, cross-category part-based object manipulation benchmark with tasks in realistic, vision-based settings and design a novel augmented state-to-vision distillation method for these challenging tasks.




    UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy

    Yinzhen Xu*, Weikang Wan*, Jialiang Zhang*, Haoran Liu*, Zikang Shan, Hao Shen, Ruicheng Wang, Haoran Geng, Yijia Weng, Jiayi Chen, Tengyu Liu, Li Yi, He Wang
    ArXiv / Project Page / Code / CVPR Page / Bibtex
    CVPR 2023

    We tackle the problem of learning universal robotic dexterous grasping from a point cloud observation under a table-top setting.

    Learning Part-Aware Visual Actionable Affordance for 3D Articulated Object Manipulation
    Yuanchen Ju*, Haoran Geng*, Ming Yang*, Yiran Geng, Yaroslav Ponomarenko, Taewhan Kim, He Wang, Hao Dong
    Paper / Video / Workshop
    CVPR 2023 @ 3DVR, Spotlight Presentation

    We introduces Part-aware Affordance Learning methods. Our approach first learns a part prior, subsequently generating an affordance map. We further enhance precision by introducing a part-level scoring system, designed to identify the best part for manipulation.




    RLAfford: End-to-End Affordance Learning for Robotic Manipulation

    Yiran Geng*, Boshi An*, Haoran Geng, Yuanpei Chen, Yaodong Yang, Hao Dong
    ArXiv / Project Page / Video / Code / Media (CFCS) / Bibtex
    ICRA 2023

    In this study, we take advantage of visual affordance by using the contact information generated during the RL training process to predict contact maps of interest.


    Before 2022


    Ministry of Education Talent Program Thesis (Physics Track)
    Haoran Geng, Yiran Geng, Xintian Dong, Yue Meng, Xujv Sun, Houpu Niu
    PDF

    I was selected for the Ministry of Education Talent Program and conducted physics research at Nankai University during my high school years.


    Services

  • Reviewer: CVPR, ICCV, NeurIPS, RSS, CoRL
  • I serve as the chair of Turing Student Research Forum 2023.
  • One of the leaders of Linux Club of Peking University(LCPU)
  • We organized High Performance Computing Integrated Competitiveness Competition and I was also the manager of the AI part.

  • Experience

    University of California, Berkeley
    2024.8 - Present
    Ph.D. Student at Berkeley AI Research (BAIR)
    Stanford University
    2023.02 - 2024.08
    Visiting Research Student through the UGVR Program
    Research Advisor: Prof. Leonidas J. Guibas
    NVIDIA GEAR Lab
    2024.2 - 2024.7
    Research Intern, lead of Humanoid Whole-body Control project
    Research Advisor: Dr. Jim Fan, Prof. Yuke Zhu
    Beijing Institute for General Artificial Intelligence (BIGAI)
    2021.12 - Present
    Research Intern
    Research Advisor: Dr. Siyuan Huang
    Academic Advisor: Prof. Song-Chun Zhu
    Visual Computing and Learning Lab(VCL)
    2022.6 - 2022.9
    Summer Research Intern
    Research Advisor: Prof. He Wang
    Academic Advisor: Prof. Baoquan Chen
    Peking University (PKU)
    2020.09 - 2024.07
    Bachelor of Science with Honors, Turing Class
    GPA ranking (Application Season GPA): 1/95
    Research Advisor: Prof. He Wang

    Selected Awards and Honors

  • 2024: Best Paper Award, RSS 2024 @ SemRob
  • 2024: Yunfan Award for Rising Star (the only undergraduate student to win this award so far), WAIC
  • 2024: Stanford Graduate Fellowship Award, Stanford
  • 2024: Berkeley Fellowship Award, UC Berkeley
  • 2024: Best Graduation Thesis Award, EECS, Peking University
  • 2024: Outstanding Graduation Thesis Scholarship, Peking University
  • 2024: Top10 Graduation Thesis (ranking 1st), EECS, Peking University
  • 2024: Outstanding Graduates of Beijing
  • 2024: Outstanding Graduates of Peking University, Peking University
  • 2023: ICCV Best Paper Award (Marr Prize) Finalist
  • 2023: Person of the Year (10 people/year), Peking University
  • 2023: Research Rising Star Award (First Price), BIGAI
  • 2023: Outstanding Overseas Exchange Scholarship
  • 2023: Academic Innovation Award of Peking University
  • 2023: May Fourth Scholarship (Highest-level Scholarship for Peking University, 125/65k+)
  • 2021-2023: Merit Student of Peking University
  • 2023: Turing Student Research Forum: Best Presentation Award & Best Poster Award
  • 2023: School of EECS Research Exhibition: Best Presentation Award
  • 2022: Center on Frontiers of Computing Studies (CFCS) Outstanding Student
  • 2022: Arawana Scholarship
  • 2021-2023: Zhongying Moral Education Scholarship
  • 2022: Turing Student Research Forum: Outstanding Presentation Award
  • 2021: National Scholarship (Highest Honor for undergraduates in China)
  • 2021: SenseTime Scholarship (Youngest winner, 30/year in China)
  • 2021: Ministry of Education Top Talent Program Scholarship

  • This homepage is designed based on Jon Barron's website and deployed on Github Pages. Last updated: Aug. 29, 2023
    © 2024 Haoran Geng