2024
Incorporating Geo-Diverse Knowledge into Prompting for
Increased Geographical Robustness in Object Recognition. Kyle
Buettner, Sina Malakouti, Xiang Lorraine Li, Adriana Kovashka. To
appear, IEEE/CVF Conference on Computer Vision and Pattern
Recognition (CVPR), June 2024.
Synonym relations affect object detection learned on
vision-language data. Giacomo Nebbia and Adriana
Kovashka. To appear, North American Chapter of the
Association for Computational Linguistics (NAACL) Findings,
June 2024.
VEIL: Vetting Extracted Image Labels from In-the-Wild Captions
for Weakly-Supervised Object Detection. Arushi Rai and Adriana
Kovashka. To appear, European Chapter
of the Association for Computational Linguistics (EACL), March
2024.
Investigating the Role of Attribute Context in Vision-Language
Models for Object Recognition and Detection. Kyle Buettner and
Adriana Kovashka. In Winter Conference on Applications
of Computer Vision (WACV), January
2024. [pdf]
Boosting Weakly Supervised Object Detection using Fusion and
Priors from Hallucinated Depth. Cagri Gungor and Adriana
Kovashka. In Winter Conference on Applications
of Computer Vision (WACV), January
2024. [pdf]
2023
Semi-Supervised Domain Generalization for Object Detection via
Language-Guided Feature Alignment. Sina Malakouti and Adriana
Kovashka. To appear, British Machine Vision Conference
(BMVC), November
2023. [pdf]
Decoding Symbolism in Language Models. Meiqi Guo, Rebecca
Hwa and Adriana Kovashka. To appear, Annual Meeting of the Association
for Computational Linguistics (ACL), July 2023. [pdf]
Hypernymization of Named Entity-rich captions for
grounding-based multi-modal pretraining. Giacomo Nebbia and
Adriana Kovashka. In ACM International Conference on
Multimedia Retrieval (ICMR), June 2023. [pdf]
Towards Shape-regularized Learning for Mitigating Texture Bias in
CNNs. Harsh Sinha and Adriana Kovashka. In ACM
International Conference on Multimedia Retrieval (ICMR), June
2023. [pdf]
Complementary Cues from Audio Help Combat Noise in
Weakly-Supervised Object Detection.
Cagri Gungor and Adriana Kovashka. In Winter Conference
on Applications of Computer Vision (WACV),
January 2023. [pdf]
How to Practice VQA on a Resource-limited Target Domain.
Mingda Zhang, Rebecca Hwa, Adriana Kovashka. In Winter
Conference on Applications of Computer Vision (WACV),
January 2023. [pdf]
Is misrecognition by teachable agents bad for students?
Yuya Asano, Diane Litman, Mingzhi Yu, Nikki Lobczowski,
Timothy Nokes-Malach, Adriana Kovashka and Erin Walker. To appear,
International Conference on Artificial Intelligence in
Education (AIED), July 2023. Poster. [pdf]
Contrastive View Design Strategies to Enhance Robustness to
Domain Shifts in Downstream Object Detection. Kyle Buettner
and Adriana Kovashka. In AAAI Workshop on Practical Deep Learning
in the Wild (AAAIW Practical-DL), February
2023. [pdf]
Improving language-supervised object detection with linguistic
structure analysis. Arushi Rai and Adriana Kovashka. To
appear, Workshop on Open-Domain Reasoning Under Multi-Modal
Settings (O-DRUM), held in conjunction with the IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), June 2023. [pdf]
2022
Learning to Overcome Noise in Weak Caption
Supervision for Object Detection. Mesut Erhan Unal, Keren Ye, Mingda Zhang, Christopher Thomas, Adriana Kovashka, Wei Li, Danfeng
Qin, Jesse Berent. In Transactions of Pattern Analysis and
Machine Intelligence (TPAMI),
2022. [pdf]
Building a Reinforcement Learning Environment from Limited Data to
Optimize Teachable Robot Interventions. Tristan Maidment,
Mingzhi Yu, Nikki Lobczowski, Adriana Kovashka, Erin Walker, Diane
Litman and Timothy Nokes-Malach. In The 15th International
Conference on Educational Data Mining (EDM), July
2022. [pdf]
Comparison of Lexical Alignment with a Teachable Robot in
Human-Robot and Human-Human-Robot Interactions. Yuya Asano,
Diane Litman, Mingzhi Yu, Nikki Lobczowski, Timothy Nokes-Malach,
Adriana Kovashka, Erin Walker. In Annual Meeting of the Special Interest Group on
Discourse and Dialogue (SIGDIAL), September
2022. [pdf]
Characterizing User Susceptibility to COVID-19 Misinformation
on Twitter. Xian Teng, Yu-Ru Lin, Wen-Ting Chung, Ang Li
and Adriana Kovashka. In International AAAI Conference
on Web and Social Media (ICWSM), June
2022. [pdf]
The Role of Shape for Domain Generalization on
Sparsely-Textured Images. Narges Honarvar Nazari and Adriana
Kovashka. In 2nd Workshop on Sketch-Oriented Deep Learning,
held in
conjunction with the IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), June
2022. [pdf]
Emphasizing Complementary Samples for Non-literal Cross-modal
Retrieval. Christopher Thomas and Adriana Kovashka. In 5th
MUltimodal Learning and Applications Workshop, held in
conjunction with the IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), June
2022. [pdf]
[supp]
Doubling down: sparse grounding with an additional,
almost-matching caption for detection-oriented multimodal
pretraining. Giacomo Nebbia and Adriana Kovashka. In 5th
MUltimodal Learning and Applications Workshop, held in
conjunction with the IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), June
2022. [pdf]
Weakly-Supervised Action Detection Guided by Audio
Narration. Keren Ye and Adriana Kovashka. In Joint 1st
Ego4D and 10th EPIC Workshop, held in
conjunction with the IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), June
2022. [pdf]
Visual Persuasion in COVID-19 Social Media Content: A
Multi-Modal Characterization. Mesut Erhan Unal, Adriana
Kovashka, Wen-Ting Chung and Yu-Ru Lin. In 1st International
Workshop on Multimodal Understanding for the Web and Social Media
(MUWS), held in conjunction with The WebConf (WWW), April
2022. [pdf]
2021
Detecting Persuasive Atypicality by Modeling Contextual
Compatibility. Meiqi Guo, Rebecca Hwa, and Adriana
Kovashka. In Proceedings of the IEEE/CVF International
Conference on Computer Vision (ICCV), October
2021. [pdf]
[supp]
Domain-robust VQA with diverse datasets and methods but no
target labels. Mingda Zhang, Tristan Maidment, Ahmad Diab,
Adriana Kovashka, Rebecca Hwa. In Proceedings of the
IEEE/CVF Conference on Computer Vision and Pattern Recognition
(CVPR), June 2021. [pdf]
Linguistic Structures as Weak Supervision for Visual Scene
Graph Generation. Keren Ye and Adriana Kovashka. In Proceedings of the
IEEE/CVF Conference on Computer Vision and Pattern Recognition
(CVPR), June 2021. [pdf]
Predicting Visual Political Bias using Webly Supervised Data
and an Auxiliary Task. Christopher Thomas and Adriana
Kovashka. In International Journal of Computer Vision
(IJCV)
2021. [preprint]
BasisNet: Two-stage Model Synthesis for Ecient Inference.
Mingda Zhang, Chun-Te Chu, Andrey Zhmoginov, Andrew Howard, Brendan
Jou, Yukun Zhu, Li Zhang, Rebecca Hwa, and Adriana Kovashka. In Proceedings of the Efficient Deep Learning for Computer
Vision Workshop (ECV), held in conjunction with the IEEE/CVF
Conference on Computer Vision and Pattern Recognition (CVPR),
June 2021. (Best Paper Award.) [pdf]
Exploring Corruption Robustness: Inductive Biases in Vision
Transformers and MLP-Mixers. Katelyn Morrison, Benjamin Gilby, Colton Lipchak, Adam Mattioli
and Adriana Kovashka. In Uncertainty and Robustness in Deep
Learning Workshop (UDL), held in conjunction with the International
Conference on Machine Learning (ICML), July
2021. [pdf]
Capturing Student-Robot Interactions for a Data-Driven
Educational Dialogue RL Environment. Tristan Maidment,
Mingzhi Yu, Erin Walker, Adriana Kovashka, Diane Litman, and
Timothy Nokes-Malach. In Reinforcement Learning for Education
Workshop (EDM-RL), held in conjunction with the Educational Data Mining
Conference, June 2021. [pdf]
Graph-Symbolic VQA with Rich Visual Estimators and No
Question-Answer Labels. Zhexiong Liu and Adriana
Kovashka. In Visual Question Answering Workshop, held in
conjunction with the IEEE/CVF
Conference on Computer Vision and Pattern Recognition (CVPR),
June 2021. [pdf]
Image retrieval with mixed initiative and multimodal
feedback. Nils Murrugarra-Llerena and Adriana
Kovashka. In Computer Vision and Image Understanding (CVIU)
Journal, March 2021. [link]
A Case Study of the Shortcut Effects in Visual Commonsense
Reasoning. Keren Ye and Adriana Kovashka.
In Proceedings of the Thirty-Fifth AAAI Conference on Artificial
Intelligence (AAAI), February
2021. [pdf]
Breaking Shortcuts by Masking for Robust Visual Reasoning.
Keren Ye, Mingda Zhang and Adriana Kovashka. In Proceedings of
the
Winter Conference on Applications of Computer Vision (WACV),
January
2021. [pdf]
[supp]
2020
Preserving Semantic Neighborhoods for Robust Cross-modal Retrieval. Christopher Thomas and Adriana Kovashka. In Proceedings of the European Conference on Computer
Vision (ECCV), August
2020. [pdf]
[video-short] [video-long]
SpotPatch: Parameter-Efficient Transfer Learning for Mobile
Object Detection. Keren Ye, Adriana Kovashka, Mark Sandler,
Menglong Zhu, Andrew Howard, Marco Fornoni. In Proceedings of the
Asian Conference on Computer Vision (ACCV), December
2020. [pdf]
Context for Object Detection via Lightweight Global and
Mid-level Representations. Mesut Erhan Unal and Adriana
Kovashka. In Proceedings of the International Conference on
Pattern Recognition (ICPR), January
2021. [pdf]
Syntharch: Interactive Image Search With Attribute-Conditioned
Synthesis. Zac Yu and Adriana Kovashka. In Proceedings of the
Diagram Image Retrieval and Analysis (DIRA), held in
conjunction with the IEEE/CVF Conference on
Computer Vision and Pattern Recognition (CVPR), June
2020. [pdf]
Story Completion With Explicit Modeling of Commonsense
Knowledge. Mingda Zhang, Keren Ye, Rebecca Hwa and Adriana
Kovashka. In Proceedings
of Minds vs. Machines: How far are we from the common sense of
a toddler?, held in conjunction with the IEEE/CVF Conference on
Computer Vision and Pattern Recognition (CVPR), June
2020. [pdf]
Domain Generalization Using Shape Representation. Narges
Honarvar Nazari and Adriana Kovashka. In Proceedings
of Transferring and Adapting Source Knowledge in Computer Vision (TASK-
CV), held in conjunction with European Conference on Computer
Vision (ECCV), August 2020.
Classifying Nuclei Shape Heterogeneity in Breast Tumors with
Skeletons. Brian Falkenstein, Adriana Kovashka, Seong Jae
Hwang and S. Chakra Chennubhotla. In Proceedings of BioImage
Computing, held in conjunction with European Conference on
Computer Vision (ECCV), August 2020.
2019
Interpreting the Rhetoric of Visual Advertisements. Keren
Ye, Narges Honarvar Nazari, James Hahn, Zaeem Hussain, Mingda Zhang,
Adriana Kovashka. In Transactions of Pattern Analysis and
Machine Intelligence (TPAMI),
2019. [pdf]
Predicting the Politics of an Image Using Webly Supervised
Data. Christopher Thomas and Adriana Kovashka. To appear,
Proceedings of the Conference on Neural Information Processing
Systems (NeurIPS), December
2019. [pdf]
[supp]
[poster] [data]
Cap2Det: Learning to Amplify Weak Caption Supervision for
Object Detection. Keren Ye, Mingda Zhang, Adriana Kovashka,
Wei Li, Danfeng Qin, Jesse Berent. To appear, Proceedings of
the International Conference on Computer Vision (ICCV),
October
2019. [pdf]
[supp]
[poster] [code]
Cross-Modality Personalization for Retrieval. Nils
Murrugarra-Llerena and Adriana Kovashka. In Proceedings of
the IEEE/CVF Conference on Computer Vision and Pattern Recognition
(CVPR), June
2019. (Oral.) [pdf]
[supp]
[poster]
[data]
Hiding in Plain Strokes: Handwriting and Applications to
Steganography. James Hahn and Adriana Kovashka. In The
Bright and Dark Sides of Computer Vision:
Challenges and Opportunities for Privacy and Security
(CV-COPS 2019), held in conjunction with the IEEE/CVF Conference on
Computer Vision and Pattern Recognition, June 2019. (Extended
Abstract.)
[pdf]
[poster]
2018
ADVISE: Symbolism and External Knowledge for Decoding
Advertisements. Keren Ye and Adriana Kovashka. In
Proceedings of the European Conference on Computer Vision (ECCV),
September
2018. [pdf]
[supp]
[related code]
Artistic Object Recognition by Unsupervised Style
Adaptation. Christopher Thomas and Adriana Kovashka. Proceedings of the Asian Conference on Computer Vision
(ACCV), December 2018. [pdf] [poster] [project page]
Image Retrieval with Mixed Initiative and Multimodal
Feedback. Nils Murrugarra-Llerena and Adriana Kovashka. In Proceedings of the British
Machine Vision Conference (BMVC), September 2018.
(Oral)
[pdf]
[supp]
Equal But Not The Same: Understanding the Implicit
Relationship Between Persuasive Images and Text. Mingda Zhang,
Rebecca Hwa and Adriana Kovashka. In Proceedings of the British
Machine Vision Conference (BMVC), September 2018.
(Spotlight)
[pdf]
[data]
Persuasive Faces: Generating Faces in Advertisements.
Christopher Thomas and Adriana Kovashka. In Proceedings of the British
Machine Vision Conference (BMVC), September 2018.
[pdf]
[supp]
Story Understanding in Video Advertisements. Keren Ye, Kyle
Buettner, Adriana Kovashka. In Proceedings of the British
Machine Vision Conference (BMVC), September 2018.
[pdf]
[data]
Asking Friendly Strangers: Non-Semantic Attribute Transfer.
Nils Murrugarra-Llerena and Adriana Kovashka. Proceedings
of the Thirty-Second AAAI Conference on Artificial
Intelligence (AAAI), February 2018. [pdf]
2017
Confidence and Diversity for Active Selection of Feedback in
Image Retrieval. Bhavin Modi and Adriana Kovashka. In
Proceedings of the British Machine Vision Conference
(BMVC), September 2017. [pdf]
Automatic Understanding of Image and Video Advertisements.
Zaeem Hussain, Mingda Zhang, Xiaozhong Zhang, Keren Ye, Christopher
Thomas, Zuha Agha, Nathan Ong, Adriana Kovashka. Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition (CVPR), July 2017. (Spotlight)
[pdf]
[supplementary]
[project
page and dataset]
[visualization]
[poster]
[spotlight]
Learning Attributes from Human Gaze. Nils Murrugarra-Llerena and Adriana Kovashka. In Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), March 2017. [pdf] [supplementary] [project page] [poster] [slides]
Detecting Sexually Provocative Images. Debashis Ganguly, Mohammad H. Mofrad and Adriana Kovashka. In Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), March 2017. [pdf] [poster] [slides]
2016
Crowdsourcing in Computer Vision. Adriana Kovashka, Olga Russakovsky, Kristen Grauman, Fei-Fei Li. In Foundations and Trends in Computer Graphics and Vision, NOW Publishers, 2016. [pdf]
Attributes for Image Retrieval. Adriana Kovashka and Kristen Grauman. In Visual Attributes (Advances in Computer Vision and Pattern Recognition), Springer, 2016.
Seeing Behind the Camera: Identifying the Authorship of a Photograph. Christopher Thomas and Adriana Kovashka. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2016. [pdf] [supplementary] [poster] [project page]
A Visual Attention Algorithm Designed for Coupled Oscillator Acceleration. Christopher Thomas, Adriana Kovashka, Donald Chiarulli and Steven Levitan. In Proceedings of The Twelfth IEEE Embedded Vision Workshop, held in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2016. (Oral) [pdf]
Inferring Visual Persuasion via Body Language, Setting, and Deep Features. Xinyue Huang and Adriana Kovashka. In Proceedings of ChaLearn Looking at People and Faces of the World Challenge and Workshop, held in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2016. (Oral) [pdf]
Adapting Attributes by Selecting Features Similar across Domains. Siqi Liu and Adriana Kovashka. In Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), March 2016. [pdf]
2015
WhittleSearch: Interactive Image Search with Relative Attribute
Feedback. Adriana Kovashka, Devi Parikh and Kristen
Grauman. International Journal of
Computer Vision (IJCV), April 2015. [link]
Discovering Attribute Shades of Meaning with the Crowd.
Adriana Kovashka and Kristen Grauman. International Journal of
Computer Vision (IJCV), January 2015. [link] [data]
2014
Interactive Image Search with Attributes. Adriana
Kovashka. PhD Thesis, 2014. [pdf]
Discovering Shades of Attribute Meaning with the Crowd. Adriana Kovashka and Kristen Grauman. Third International Workshop on Parts and Attributes, held in conjunction with the European Conference on Computer Vision (ECCV), September 2014. [pdf]
Discovering Shades of Attribute Meaning with the Crowd. Adriana Kovashka and Kristen Grauman. Technical Report AI13-02, The University of Texas at Austin, November 5, 2013. [pdf]
Interactive Image Search with Attribute-based Guidance and Personalization. Adriana Kovashka and Kristen Grauman. Workshop on Computer Vision and Human Computation, held in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2014. [pdf]
2013
Attribute Adaptation for Personalized Image Search. Adriana Kovashka and Kristen Grauman. Proceedings of the International Conference on Computer Vision (ICCV), December 2013. [pdf] [supplementary] [poster] [project page]
Attribute Pivots for Guiding Relevance Feedback in Image Search. Adriana Kovashka and Kristen Grauman. Proceedings of the International Conference on Computer Vision (ICCV), December 2013. [pdf] [supplementary] [poster] [project page]
2012
WhittleSearch: Image Search with Relative Attribute Feedback. Adriana Kovashka, Devi Parikh and Kristen Grauman. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2012. [pdf] [supplementary] [poster] [project page]
[demo]
Relative Attributes for Enhanced Human-Machine Communication (Invited paper). Devi Parikh, Adriana Kovashka, Amar Parkash and Kristen Grauman. AAAI Conference on Artificial Intelligence (AAAI), July 2012. [pdf]
2011
Actively Selecting Annotations Among Objects and Attributes. Adriana Kovashka, Sudheendra Vijayanarasimhan and Kristen Grauman. Proceedings of the International Conference on Computer Vision (ICCV), November 2011. [pdf] [poster] [video] [project page]
2010
Learning a Hierarchy of Discriminative Space-Time Neighborhood Features for Human Action Recognition. Adriana Kovashka and Kristen Grauman. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2010. [pdf] [project page] [poster]
Authorship Attribution Using Probabilistic Context-Free Grammars. Sindhu Raghavan, Adriana Kovashka and Raymond Mooney. Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL), Short Papers, July 2010. [pdf]
Human and Machine Detection of Stylistic Similarity in Art. Adriana Kovashka and Matthew Lease. CrowdConf 2010, October 2010. [pdf]