Ramakrishna Vedantam
Ramakrishna Vedantam
Research Scientist, Facebook AI Research
Verified email at fb.com - Homepage
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
3667*2016
CIDEr: Consensus-based Image Description Evaluation
R Vedantam, CL Zitnick, D Parikh
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, 2014
16052014
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
8292015
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
942017
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
822016
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
772015
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
762015
Generative Models of Visually Grounded Imagination
R Vedantam, I Fischer, J Huang, K Murphy
International Conference on Learning Representations (ICLR), 2018, 2018
752018
Adopting abstract images for semantic scene understanding
CL Zitnick, R Vedantam, D Parikh
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014
732014
Probabilistic neural-symbolic models for interpretable visual question answering
R Vedantam, K Desai, S Lee, M Rohrbach, D Batra, D Parikh
arXiv preprint arXiv:1902.07864, 2019
222019
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
172017
CURI: A Benchmark for Productive Concept Learning Under Uncertainty
R Vedantam, A Szlam, M Nickel, A Morcos, B Lake
arXiv preprint arXiv:2010.02855, 2020
22020
Learning Optimal Representations with the Decodable Information Bottleneck
Y Dubois, D Kiela, DJ Schwab, R Vedantam
arXiv preprint arXiv:2009.12789, 2020
2020
DS-VIC: Unsupervised Discovery of Decision States for Transfer in RL
N Modhe, P Chattopadhyay, M Sharma, A Das, D Parikh, D Batra, ...
arXiv preprint arXiv:1907.10580, 2019
2019
Evaluating the Compositionality Gap for Productive Concept Learning
R Vedantam, A Szlam, M Nickel, A Morcos, B Lake
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Articles 1–15