Luming Tang (唐路明)

I am a final-year Computer Science PhD candidate at Cornell University, advised by Professor Bharath Hariharan. Before that, I received my Bachelor degree in Mathematics and Physics from Tsinghua University.

I am currently on the job market, looking for a research scientist / engineer or post-doc job starting from mid-2024. Feel free to contact me if you have any openings.

Email  /  Resume  /  GitHub  /  Google Scholar  /  Twitter  /  LinkedIn

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Research

My current interests lie at the intersection of machine learning and computer vision, including representation learning and generative models, especially on how to adapt large pre-trained models to tackle challenging real-world problems where data is constrained. Meanwhile, I'm also interested in building vision foundation models.

(* indicates equal contribution)

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RealFill: Reference-Driven Generation for Authentic Image Completion


Luming Tang, Nataniel Ruiz, Qinghao Chu, Yuanzhen Li, Aleksander Holynski, David E. Jacobs, Bharath Hariharan, Yael Pritch, Neal Wadhwa, Kfir Aberman, Michael Rubinstein
Tech Report, 2023
paper / video / project page

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Emergent Correspondence from Image Diffusion


Luming Tang*, Menglin Jia*, Qianqian Wang*, Cheng Perng Phoo, Bharath Hariharan
NeurIPS, 2023
paper / video / code / poster / slides / project page

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Magic3D: High-Resolution Text-to-3D Content Creation


Chen-Hsuan Lin*, Jun Gao*, Luming Tang*, Towaki Takikawa*, Xiaohui Zeng*, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin
CVPR, 2023 (Highlight)
paper / project page

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Visual Prompt Tuning


Menglin Jia*, Luming Tang*, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, Ser-Nam Lim
ECCV, 2022
paper / video / code

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Few-Shot Classification with Feature Map Reconstruction Networks


Davis Wertheimer*, Luming Tang*, Bharath Hariharan
CVPR, 2021
paper / video / code / poster

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Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition


Luming Tang, Davis Wertheimer, Bharath Hariharan
CVPR, 2020
paper / video / code / slides

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Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder


Luming Tang, Yexiang Xue, Di Chen, Carla P. Gomes
AAAI, 2018
paper / code / poster / slides

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Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-identification


Zhongdao Wang*, Luming Tang*, Xihui Liu, Zhuliang Yao, Shuai Yi, Jing Shao, Junjie Yan, Shengjin Wang, Hongsheng Li, Xiaogang Wang
ICCV, 2017
paper / dataset / poster

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Hierarchical Deep Recurrent Architecture for Video Understanding


Luming Tang, Boyang Deng, Haiyu Zhao, Shuai Yi
CVPR Workshop on Youtube-8M Large-Scale Video Understanding, 2017
paper / code


Projects

Here're some interesting research or course projects I have worked on.

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Diagnosing and Remedying Shot Sensitivity with Cosine Few-Shot Learners


Davis Wertheimer*, Luming Tang*, Bharath Hariharan
Tech Report, 2022
arxiv

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Few-Shot Learning in Long-Tailed Settings


Davis Wertheimer, Luming Tang, Dhruv Baijal, Pranjal Mittal, Anika Talwar, Bharath Hariharan
Tech Report, 2021
paper / code

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Baseline implementation of DrQA and BERT finetuning on SQuAD 2.0


Luming Tang
CS 5740 Natural Language Processing, Assignment 4, 2020
code

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An Experimental Evaluation of Optimized Maximum Flow Implementations


Junxi Song, Luming Tang, Hongbo Zhang, Xiaoji Zhang (alphabetical order)
CS 6820 Analysis of Algorithms, Course Project, 2019
draft

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Garbage Collection Schedule Algorithm


Luming Tang*, Junxi Song*
CS 6820 Analysis of Algorithms, Assignment 2 Problem 4, 2019
problem / our proof

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On the Regularization Balance in Autoencoder-Based Generative Models


Bin Dai, Luming Tang, David Wipf
Tech Report, 2019
draft / supplementary

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OpenNRE: An Open-Source Package for Neural Relation Extraction


Tianyu Gao, Xu Han, Shulin Cao, Luming Tang, Yankai Lin, Zhiyuan Liu
THUNLP Github, 2018
code


Experience

I am very fortunate to have chance to work in multiple great research groups and spend enjoyable time with so many amazing advisors, mentors and collaborators.

Service

Teaching Assistant:

PhD admission committee student volunteer: 2020, 2023

Conference Reviewer: CVPR'21 (Outstanding Reviewer), ICCV'21, CVPR'22, ECCV'22, CVPR'23, ICCV'23, ICML'23, NeurIPS'23, ICLR'24, ICML'24, CVPR'24

Journal Reviewer: TPAMI-SI (Learning with Fewer Labels), IJCV

PC member: AAAI'23

Misc.

  • Header avatars credit to Zeya Peng.
  • I love playing soccer and FIFA (FIFA'20 Season Division 1 with Title, FIFA'22 Ultimate Team Division 3).
  • Meet the most adorable S'more and check out her instagram! Her Chinese name is 屎妹 :) This is her best friend, Shiba a.k.a. 屎宝 lol.
  • I am from Jiaozuo, a beautiful small city in Henan, China.

Design and source code modified based on Leonid Keselman and Jon Barron's website

last update: Nov, 2023