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Ramakrishna Vedantam
Ramakrishna Vedantam
Self Employed; Prev: Meta AI (FAIR)
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Title
Cited by
Cited by
Year
Grad-CAM: Why did you say that?
RR Selvaraju, A Das, R Vedantam, M Cogswell, D Parikh, D Batra
IEEE International Conference on Computer Vision (ICCV), 2017, 2016
23180*2016
CIDEr: Consensus-based Image Description Evaluation
R Vedantam, CL Zitnick, D Parikh
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, 2014
47662014
Microsoft coco captions: Data collection and evaluation server
X Chen, H Fang, TY Lin, R Vedantam, S Gupta, P Dollár, CL Zitnick
arXiv preprint arXiv:1504.00325, 2015
25052015
Counting Everyday Objects in Everyday Scenes
P Chattopadhyay, R Vedantam, RS Ramprasaath, D Batra, D Parikh
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, 2016
1772016
Context-aware captions from context-agnostic supervision
R Vedantam, S Bengio, K Murphy, D Parikh, G Chechik
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, 2017
1642017
Generative Models of Visually Grounded Imagination
R Vedantam, I Fischer, J Huang, K Murphy
International Conference on Learning Representations (ICLR), 2018, 2018
1562018
Visual Word2Vec (vis-w2v): Learning Visually Grounded Word Embeddings Using Abstract Scenes
S Kottur, R Vedantam, JMF Moura, D Parikh
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, 2015
1192015
Learning Common Sense Through Visual Abstraction
R Vedantam, X Lin, T Batra, CL Zitnick, D Parikh
IEEE International Conference on Computer Vision (ICCV), 2015, 2015
1052015
Probabilistic neural symbolic models for interpretable visual question answering
R Vedantam, K Desai, S Lee, M Rohrbach, D Batra, D Parikh
International Conference on Machine Learning, 6428-6437, 2019
1002019
Adopting abstract images for semantic scene understanding
CL Zitnick, R Vedantam, D Parikh
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014
992014
Microsoft coco captions: Data collection and evaluation server. arXiv 2015
X Chen, H Fang, TY Lin, R Vedantam, S Gupta, P Dollár, CL Zitnick
arXiv preprint arXiv:1504.00325 2, 2015
662015
Learning optimal representations with the decodable information bottleneck
Y Dubois, D Kiela, DJ Schwab, R Vedantam
Advances in Neural Information Processing Systems 33, 18674-18690, 2020
402020
Hyperbolic image-text representations
K Desai, M Nickel, T Rajpurohit, J Johnson, SR Vedantam
International Conference on Machine Learning, 7694-7731, 2023
332023
An empirical investigation of domain generalization with empirical risk minimizers
R Vedantam, D Lopez-Paz, DJ Schwab
Advances in neural information processing systems 34, 28131-28143, 2021
332021
Sound-word2vec: Learning word representations grounded in sounds
AK Vijayakumar, R Vedantam, D Parikh
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017, 2017
312017
Curi: A benchmark for productive concept learning under uncertainty
R Vedantam, A Szlam, M Nickel, A Morcos, BM Lake
International Conference on Machine Learning, 10519-10529, 2021
272021
Improving selective visual question answering by learning from your peers
C Dancette, S Whitehead, R Maheshwary, R Vedantam, S Scherer, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
122023
COAT: Measuring Object Compositionality in Emergent Representations.
S Xie, AS Morcos, SC Zhu, R Vedantam
ICML, 24388-24413, 2022
82022
Understanding the detrimental class-level effects of data augmentation
P Kirichenko, M Ibrahim, R Balestriero, D Bouchacourt, SR Vedantam, ...
Advances in Neural Information Processing Systems 36, 2024
5*2024
Embarrassingly simple dataset distillation
Y Feng, SR Vedantam, J Kempe
The Twelfth International Conference on Learning Representations, 2023
52023
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