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Large-Scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline

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Computer Vision – ECCV 2020 (ECCV 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12363))

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Abstract

Prior work in visual dialog has focused on training deep neural models on VisDial in isolation. Instead, we present an approach to leverage pretraining on related vision-language datasets before transferring to visual dialog. We adapt the recently proposed ViLBERT model for multi-turn visually-grounded conversations. Our model is pretrained on the Conceptual Captions and Visual Question Answering datasets, and finetuned on VisDial. Our best single model outperforms prior published work by \(1\%\) absolute on NDCG and MRR.

Next, we find that additional finetuning using “dense” annotations in VisDial leads to even higher NDCG – more than \(10\%\) over our base model – but hurts MRR – more than \(17\%\) below our base model! This highlights a trade-off between the two primary metrics – NDCG and MRR – which we find is due to dense annotations not correlating well with the original ground-truth answers to questions.

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Notes

  1. 1.

    Publicly available on visualdialog.org/data.

  2. 2.

    github.com/vmurahari3/visdial-bert/.

  3. 3.

    Along with code released at github.com/jiasenlu/ViLBERT_beta.

  4. 4.

    Publicly available on visualdialog.org/data.

  5. 5.

    evalai.cloudcv.org/web/challenges/challenge-page/161/leaderboard/483.

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Acknowledgments

The Georgia Tech effort was supported in part by NSF, AFRL, DARPA, ONR YIPs, ARO PECASE, Amazon. AD was supported by fellowships from Facebook, Adobe, Snap Inc. Views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. Government, or any sponsor.

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Authors and Affiliations

  1. Georgia Institute of Technology, Atlanta, USA

    Vishvak Murahari, Dhruv Batra, Devi Parikh & Abhishek Das

  2. Facebook AI Research, Menlo Park, USA

    Dhruv Batra, Devi Parikh & Abhishek Das

Authors
  1. Vishvak Murahari
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  2. Dhruv Batra
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  3. Devi Parikh
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  4. Abhishek Das
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Corresponding author

Correspondence to Vishvak Murahari .

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Editors and Affiliations

  1. University of Oxford, Oxford, UK

    Andrea Vedaldi

  2. Graz University of Technology, Graz, Austria

    Horst Bischof

  3. University of Freiburg, Freiburg im Breisgau, Germany

    Thomas Brox

  4. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Jan-Michael Frahm

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Murahari, V., Batra, D., Parikh, D., Das, A. (2020). Large-Scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, JM. (eds) Computer Vision – ECCV 2020. ECCV 2020. Lecture Notes in Computer Science(), vol 12363. Springer, Cham. https://doi.org/10.1007/978-3-030-58523-5_20

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  • DOI: https://doi.org/10.1007/978-3-030-58523-5_20

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