Luming Tang (唐路明)

I am a Research Scientist at Google DeepMind in New York City. Previously, I was a CS PhD student at Cornell University, advised by Professor Bharath Hariharan. Before that, I received my Bachelor degree in Mathematics and Physics from Tsinghua University.

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Research

(* indicates equal contribution)

Unified Autoregressive Visual Generation and Understanding with Continuous Tokens

Coarse Correspondences Boost Spatial-Temporal Reasoning in Multimodal Language Model

RealFill: Reference-Driven Generation for Authentic Image Completion

Emergent Correspondence from Image Diffusion

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

Visual Prompt Tuning

Few-Shot Classification with Feature Map Reconstruction Networks

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

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

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

Hierarchical Deep Recurrent Architecture for Video Understanding

Projects

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

Diagnosing and Remedying Shot Sensitivity with Cosine Few-Shot Learners

Few-Shot Learning in Long-Tailed Settings

Baseline implementation of DrQA and BERT finetuning on SQuAD 2.0

An Experimental Evaluation of Optimized Maximum Flow Implementations

Garbage Collection Schedule Algorithm

On the Regularization Balance in Autoencoder-Based Generative Models

OpenNRE: An Open-Source Package for Neural Relation Extraction

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.

• May 2019 - Now: Graphics and Vision Group, Cornell
  Graduate Research Assistant, advised by Bharath Hariharan, collaborate with Davis Wertheimer, Menglin Jia, Qianqian Wang, Cheng Perng Phoo
• May 2023 - Now: Google Research
  Research Intern, hosted by Neal Wadhwa, Nataniel Ruiz, Michael Rubinstein, collaborate with Qinghao Chu, Yuanzhen Li, Aleksander Holynski, David E. Jacobs, Yael Pritch, Kfir Aberman
• May 2022 - Feb 2023: NVIDIA Research
  Research Intern, mentored by Tsung-Yi Lin, collaborated with Chen-Hsuan Lin, Ming-Yu Liu, Xiaohui Zeng, Karsten Kreis, Xun Huang, Jun Gao, Towaki Takikawa
• May 2021 - Nov 2021: Perception Group, Waymo
  Intern, mentored by Shiwei Sheng, Andy Tsai, Ruichi Yu, collaborated with Frederick Liu, Xu Chen, Charles Qi
• Sep 2018 - Dec 2018: Visual Computing Group, Microsoft Research Asia
  Research Intern, mentored by David Wipf, collaborated with Bin Dai
• Sep 2016 - Jun 2018: Natural Language Processing Lab, Tsinghua
  Undergraduate Research Assistant, advised by Zhiyuan Liu
• Jun 2017 - Sep 2017: Computational Sustainability Lab, Cornell
  Research Intern, advised by Carla Gomes, collaborated with Yexiang Xue, Di Chen

Service

Teaching Assistant:

• Spring 2019, CS 4787 Principles of Large-Scale Machine Learning
• Summer 2019, CS 2110 OOP and Data Structures
• Fall 2019, CS 6670 Graduate Computer Vision

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, ECCV'24, SIGGRAPH Asia’24, SIGGRAPH’25, CVPR'25

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

PC member: AAAI'23

Misc.

• 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 :)
• 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: Mar, 2025