ArXiv Manuscripts

1. Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollar, C. Lawrence Zitnick
   Microsoft COCO Captions: Data Collection and Evaluation Server
   [April, 2015]

Publications

1. Yann Dubois, Douwe Keila, David J. Schwab, Ramakrishna Vedantam
   Learning Optimal Representations with the Decodable Information Bottleneck
   Neural Information Processing Systems (NeurIPS), 2020 (Spotlight) [Top 4%]
   
2. Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam
   IR-VIC: IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL
   International Joint Conference on Artificial Intelligence (IJCAI), 2020 [Top 12.6%]
   
3. Ramakrishna Vedantam
   Interpretation, Grounding and Imagination for Machine Intelligence
   Ph.D. Thesis
   
4. Ramakrishna Vedantam, Karan Desai, Stefan Lee, Marcus Rohrbach, Dhruv Batra, Devi Parikh
   Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering
   International Conference on Machine Learning (ICML), 2019 (Long Oral) [Top 4.2%]
   
5. Ramakrishna Vedantam, Ian Fischer, Jonathan Huang, Kevin Murphy
   Generative Models of Visually Grounded Imagination
   International Conference on Learning Representations (ICLR), 2018 [Top 10%]
   [Code]
   
6. Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra
   Grad-CAM: Why did you say that? Visual Explanations from Deep Networks via Gradient-based Localization
   International Conference on Computer Vision (ICCV), 2017
   [Code][Blog][Demo]
7. Ashwin K. Vijayakumar, Ramakrishna Vedantam, Devi Parikh
   Sound-Word2Vec: Learning Word Representations Grounded in Sounds
   Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017 (Short)
   
8. Prithvijit Chattopadhyay^*, Ramakrishna Vedantam^*, Ramprasaath RS, Dhruv Batra, Devi Parikh
   Counting Everyday Objects in Everyday Scenes
   IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 (Spotlight) [Top 8.2%]
   [Code]
9. Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik
   Context-aware Captions from Context-agnostic Supervision
   IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 (Spotlight) [Top 8.2%]
   [Project Page] [arXiv]
   
10. Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, Dhruv Batra
    Grad-CAM: Why did you say that? Visual Explanations from Deep Networks via Gradient-based Localization
    NIPS Workshop on Interpretable Machine Learning in Complex Systems, 2016
    
11. C. Lawrence Zitnick, Ramakrishna Vedantam, Devi Parikh
    Adopting Abstract Images for Semantic Scene Understanding
    Special Issue on the best papers at the 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2016
12. Satwik Kottur^*, Ramakrishna Vedantam^*, Jose´ Moura, Devi Parikh
    Visual Word2Vec (vis-w2v): Learning Visually Grounded Word Embeddings Using Abstract Scenes
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
    [Project Page] [Code] [arXiv]
13. Ramakrishna Vedantam^*, Xiao Lin^*, Tanmay Batra, C. Lawrence Zitnick, Devi Parikh
    Learning Common Sense Through Visual Abstraction
    IEEE International Conference on Computer Vision (ICCV), 2015
    [Project page] [Code]
    
14. Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh
    CIDEr: Consensus-based Image Description Evaluation
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
    [Project Page] [Code][arXiv]
    

^* Equal Contribution