Bryan A. Plummer

Assistant Professor
Image and Video Computing Group
Department of Computer Science
Boston University
Office: CDS844
Email: bplum@bu.edu

CV, Google Scholar, Github

Summer 2024 REU opportunities available:
   Apply here for non-BU students.
   Apply here for BU students (masters also eligible).


My research interests fall within the umbrella of artificial intelligence with a focus on visual recognition, scene recognition, interpretable and fair machine learning, and understanding the relationship between vision and language.

As of July 2020 I am an Assistant Professor in the Department of Computer Science at Boston University and a core faculty member of the Artificial Intelligence Research (AIR) initiative at the Rafik B. Hariri Institute for Computing and Computational Science & Engineering. I obtained my PhD in the computer vision group at the University of Illinois at Urbana-Champaign advised by Svetlana Lazebnik. After that I worked as a Postdoctoral Associate with Kate Saenko and Stan Sclaroff and later as a Research Assistant Professor before my current position. During my PhD I was fortunate to be named a 3M Foundation Fellow, NSF GRFP honorable mention, and was able to spend my summers working with Hadi Kiapour (eBay), Shuai Zheng (eBay), Robinson Piramuthu (eBay), Matthew Brown (Google), Himanshu Arora (A9), and Stephen Kelley (MIT Lincoln Labs).

Recent News

  • My student's paper proposing a unifed human image maniuplation model and dataset and another student's paper that learns to convert a model trained on short clips to understand much longer videos was accepted at CVPR 2024
  • I will be serving as an Area Chair for ECCV'24
  • My student's paper on improving question answering with debating LLMs was accepted at ICLR 2024
  • My student Andrea Burns has defended her PhD thesis! Congratulations Dr. Burns!
  • My students have 4 papers accepted to WACV 2024: a paper on efficient ensembling, a paper on reducing training time by growing a network over time, a paper on improving text-to-image image maniuplation, and a paper that identifies important video clips and keywords in language for movie genre classification
  • My student's paper exploring multimodal webpage understanding and another student's paper that proposes an entity-aware model for article understanding was accepted at EMNLP 2023
  • I will be serving as an Area Chair for CVPR'24
  • My student's paper introducing a new research topic on channel-adaptive imaging models and another student's paper that explores compositional image-text understanding was accepted at NeurIPS 2023
  • My student's paper on performing text-to-image editing by leverging scene graphs was accepted at BMVC 2023
  • My student's paper proposing an approach for human pose transfer without paired training data was accepted at ICCV 2023
  • Thanks to Meta for supporting our research
  • I will be serving as an Area Chair for NeurIPS'23

PhD Students

Other Current Students

  • Harsh Khatri (masters)
  • Elly (Yitong) Wang (undergrad)

Former Students

  • Andrea Burns (with Kate Saneko), PhD 2023, now at Google Research
  • Nishant Nadkarni (masters, 2023)
  • Duruvan Saravanan (masters, 2023)
  • Divya Appapogu (masters, 2022)
  • Ashlesha Chaudhari (masters, 2022)
  • Soren Nelson (masters, 2022)
  • Zora Che (undergrad, 2022), continuing as a PhD student at University of Maryland, College Park
  • John (Yuanming) Chai (undergrad, 2022)
  • Murt Al Bahrani (masters, 2021)
  • Julius Frost (BA/MS, 2021, with Kate Saenko), now at MORSE Corp
  • Sanjna Agrawal (undergrad, 2021)
  • Yize Xie (masters, 2020)
  • Farheen Rahman (undergrad, 2020)
  • Tammy Qiu (undergrad, 2019, with Kate Saenko), now a PhD student at Columbia University
  • Paige Kordas (undergrad, 2018, with David Forsyth), now at Facebook

Teaching


Publications Grouped by Topic

Go here for publications by year

Visual Grounding




   

Maan Qraitem, Bryan A. Plummer. From Coarse to Fine-grained Concept based Discrimination for Phrase Detection. CVPR Workshop on Computer Vision in the Wild, 2023. [paper][bibtex]



   

Reuben Tan, Bryan A. Plummer, Kate Saenko, Hailin Jin, Bryan Russell. Look at What I’m Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos. NeurIPS, 2021. [paper][bibtex]



   

Bryan A. Plummer, Kevin J. Shih, Yichen Li, Ke Xu, Svetlana Lazebnik, Stan Sclaroff, Kate Saenko. Revisiting Image-Language Networks for Open-ended Phrase Detection. TPAMI, 44(4):2155-2167, 2022. [paper][code][bibtex]



   

Bryan A. Plummer, Paige Kordas, M. Hadi Kiapour, Shuai Zheng, Robinson Piramuthu, Svetlana Lazebnik. Conditional Image-Text Embedding Networks. ECCV, 2018. [paper][code][bibtex]



   

Bryan A. Plummer, Arun Mallya, Christopher M. Cervantes, Julia Hockenmaier, Svetlana Lazebnik. Phrase Localization and Visual Relationship Detection with Comprehensive Image-Language Cues. ICCV, 2017. [paper][code][bibtex]



   

Bryan A. Plummer, Liwei Wang, Christopher M. Cervantes, Juan C. Caicedo, Julia Hockenmaier, Svetlana Lazebnik. Flickr30K Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models. IJCV, 123(1):74-93, 2017. [paper][project][bibtex]

Bryan A. Plummer, Liwei Wang, Christopher M. Cervantes, Juan C. Caicedo, Julia Hockenmaier, Svetlana Lazebnik. Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models. ICCV, 2015. [paper][project][bibtex]




Long Article Understanding




   

Zhongping Zhang, Yiwen Gu, Bryan A. Plummer. Show, Write, and Retrieve: Entity-aware Article Generation and Retrieval. Findings of EMNLP, 2023. [paper][code][bibtex]



   

Reuben Tan, Bryan A. Plummer, Kate Saenko, J. P. Lewis, Avneesh Sud, Thomas Leung. NewsStories: Illustrating articles with visual summaries. ECCV, 2022. [paper][project][bibtex]



   

Reuben Tan, Bryan A. Plummer, Kate Saenko. Detecting Cross-Modal Inconsistency to Defend Against Neural Fake News. EMNLP, 2020. [paper][project][bibtex]




Vision and Language




   

Reuben Tan, Ximeng Sun, Ping Hu, Jui-hsien Wang, Hanieh Deilamsalehy, Bryan A. Plummer, Bryan Russell, Kate Saenko. VideoMosaic: Connecting the Temporal Dots in Long Videos for LLMs. CVPR, 2024. [pdf coming soon][bibtex]



   

Zhongping Zhang, Yiwen Gu, Bryan A. Plummer, Xin Miao, Jiayi Liu, Huayan Wang. Movie Genre Classification by Language Augmentation and Shot Sampling. WACV, 2024. [paper][code][bibtex]



   

Andrea Burns, Krishna Srinivasan, Joshua Ainslie, Geoff Brown, Bryan A. Plummer, Kate Saenko, Jianmo Ni, Mandy Guo. A Suite of Generative Tasks for Multi-Level Multimodal Webpage Understanding. EMNLP, 2023. [paper][data][bibtex]



   

Arijit Ray, Filip Radenovic, Abhimanyu Dubey, Bryan A. Plummer, Ranjay Krishna, Kate Saenko. Cola: A Benchmark for Compositional Text-to-image Retrieval. NeurIPS Track on Datasets and Benchmarks, 2023. [paper][code][bibtex]



   

Reuben Tan, Arijit Ray, Andrea Burns, Bryan A. Plummer, Justin Salamon, Oriol Nieto, Bryan Russell, Kate Saenko. Language-Guided Audio-Visual Source Separation via Trimodal Consistency. CVPR, 2023. [paper][project][bibtex]



   

Andrea Burns, Deniz Arsan, Sanjna Agrawal, Ranjitha Kumar, Kate Saenko, Bryan A. Plummer. A Dataset for Interactive Vision-Language Navigation with Unknown Command Feasibility. ECCV, 2022. [paper][code&data][bibtex]



   

Reuben Tan, Huijuan Xu, Kate Saenko, Bryan A. Plummer. LoGAN: Latent Graph Co-Attention Network for Weakly-Supervised Video Moment Retrieval. WACV, 2021. [paper][bibtex]



   

Huijuan Xu, Kun He, Bryan A. Plummer, Leonid Sigal, Stan Sclaroff, Kate Saenko. Multilevel Language and Vision Integration for Text-to-Clip Retrieval. AAAI, 2019. [paper][code][bibtex]



   

Tatiana Tommasi, Arun Mallya, Bryan A. Plummer, Svetlana Lazebnik, Alexander C. Berg, Tamara L. Berg. Combining Multiple Cues for Visual Madlibs Question Answering. IJCV, 127(1):38-60, 2019. [paper][bibtex]

Tatiana Tommasi, Arun Mallya, Bryan A. Plummer, Svetlana Lazebnik, Alexander C. Berg, Tamara L. Berg. Solving Visual Madlibs with Multiple Cues. BMVC, 2016. [paper][bibtex]



   

Bryan A. Plummer, Matthew Brown, Svetlana Lazebnik. Enhancing Video Summarization via Vision-Language Embedding. CVPR, 2017. [paper][bibtex]




Controllable Image Manipulation




   

Nannan Li, Qing Liu, Krishna Kumar Singh, Yilin Wang, Jianming Zhang, Bryan A. Plummer, Zhe Lin. UniHuman: A Unified Model for Editing Human Images in the Wild. CVPR, 2024. [paper][bibtex]



   

Zhongping Zhang, Jian Zheng, Jacob Zhiyuan Fang, Bryan A. Plummer. Text-to-image Editing by Image Information Removal. WACV, 2024. [paper][bibtex]



   

Zhongping Zhang, Huiwen He, Bryan A. Plummer, Zhenyu Liao, Huayan Wang. Complex Scene Image Editing by Scene Graph Comprehension. BMVC, 2023. [paper][code][bibtex]



   

Nannan Li, Kevin J. Shih, Bryan A. Plummer. Collecting The Puzzle Pieces: Disentangled Self-Driven Human Pose Transfer by Permuting Textures. ICCV, 2023. [paper][code][bibtex]



   

Nannan Li, Bryan A. Plummer. Supervised Attribute Information Removal and Reconstruction for Image Manipulation. ECCV, 2022. [paper][code][bibtex]




Efficient Neural Networks




   

Piotr Teterwak*, Soren Nelson*, Nikoli Dryden, Dina Bashkirova, Kate Saenko, Bryan A. Plummer. Learning to Compose SuperWeights for Neural Parameter Allocation Search. WACV, 2024. [paper][code][bibtex]



   

Chau Pham*, Piotr Teterwak*, Soren Nelson*, Bryan A. Plummer. MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters. WACV, 2024. [paper][code][bibtex]



   

Bryan A. Plummer*, Nikoli Dryden*, Julius Frost, Torsten Hoefler, Kate Saenko. Neural Parameter Allocation Search. ICLR, 2022. [paper][code][video][bibtex]



   

Donghyun Kim, Tian Lan, Chuhang Zou, Ning Xu, Bryan A. Plummer, Stan Sclaroff, Jayan Eledath, Gerard Medioni. Multi-Task Learning from Videos via Efficient Inter-Frame Attention. ICCV Workshops, 2021. [paper][bibtex]




Fair and Explainable AI




   

Maan Qraitem, Kate Saenko, Bryan A. Plummer. Bias Mimicking: A Simple Sampling Approach for Bias Mitigation. CVPR, 2023. [paper][code][bibtex]



   

Olivia Watkins, Sandy Huang, Julius Frost, Kush Bhatia, Eric Weiner, Pieter Abbeel, Trevor Darrell, Bryan A. Plummer, Kate Saenko, Anca Dragan. Explaining robot policies. Applied AI Letters, 2021. [paper][bibtex]



   

Bryan A. Plummer*, Mariya I. Vasileva*, Vitali Petsiuk, Kate Saenko, David Forsyth. Why do These Match? Explaining the Behavior of Image Similarity Models. ECCV, 2020. [paper][code][supplementary][bibtex]




Image Similarity and Search




   

Zitong Chen*, Chau Pham*, Siqi Wang, Michael Doron, Nikita Moshkov, Bryan A. Plummer, Juan C Caicedo. CHAMMI: A benchmark for channel-adaptive models in microscopy imaging. NeurIPS Track on Datasets and Benchmarks, 2023. [paper][code][data][bibtex]



   

Samarth Mishra*, Zhongping Zhang*, Yuan Shen, Ranjitha Kumar, Venkatesh Saligrama, Bryan A. Plummer. Effectively Leveraging Attributes for Visual Similarity. ICCV, 2021. [paper][code][bibtex]



   

Donghyun Kim, Kuniaki Saito, Samarth Mishra, Stan Sclaroff, Kate Saenko, Bryan A. Plummer. Self-Supervised Visual Attribute Learning for Fashion Compatibility. ICCV Workshops, 2021. [paper][bibtex]



   

Reuben Tan, Mariya I. Vasileva, Kate Saenko, Bryan A. Plummer. Learning Similarity Conditions Without Explicit Supervision. ICCV, 2019. [paper][code][bibtex]



   

Bryan A. Plummer, M. Hadi Kiapour, Shuai Zheng, Robinson Piramuthu. Give me a hint! Navigating Image Databases using Human-in-the-loop Feedback. WACV, 2019. [paper][bibtex]



   

Mariya I. Vasileva, Bryan A. Plummer, Krishna Dusad, Shreya Rajpal, Ranjitha Kumar, David Forsyth. Learning Type-Aware Embeddings for Fashion Compatibility. ECCV, 2018. [paper][code][bibtex]




Collaborative Agents




   

Chau Pham*, Boyi Liu*, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang. Let Models Speak Ciphers: Multiagent Debate through Embeddings. ICLR, 2024. [paper][code][bibtex]




Domain Adaptation/Transfer Learning




   

Donghyun Kim, Kuniaki Saito, Tae-Hyun Oh, Bryan A. Plummer, Stan Sclaroff, Kate Saenko. CDS: Cross-Domain Self-supervised Pre-training. ICCV, 2021. [paper][bibtex]



   

P. Daphne Tsatsoulis, Bryan A. Plummer, David Forsyth. Visual Analogies: A Framework for Defining Aspect Categorization. ECCV TASK-CV Workshop, 2016. Workshop Best Paper Award. [paper][bibtex]




Language Representation Learning




   

Andrea Burns, Donghyun Kim, Derry Wijaya, Kate Saenko, Bryan A. Plummer. Learning to Scale Multilingual Representations for Vision-Language Tasks. ECCV, 2020. [paper][project][supplementary][bibtex]



   

Donghyun Kim, Kuniaki Saito, Kate Saenko, Stan Sclaroff, Bryan A. Plummer. MULE: Multimodal Universal Language Embedding. AAAI, 2020. [paper][project][code][bibtex]



   

Andrea Burns, Reuben Tan, Kate Saenko, Stan Sclaroff, Bryan A. Plummer. Language Features Matter: Effective Language Representations for Vision-Language Tasks. ICCV, 2019. [paper][project][bibtex]