Publications (Computer Vision)

Pan, B., Panda, R., Jin, S., Feris, R., Oliva, A., Isola, P., & Kim, Y. (2023). LangNav: Language as a Perceptual Representation for Navigation. Submitted arXiv Paper

Sun, X., Panda, R., Chen, C-F., Wang, N., Pan, B., Oliva, A., Rogerio, R., & Saenko, K. (2023). Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths. In Press, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2024) arXiv Paper Paper

Cascante-Bonilla, P., Shehada, K., Smith, J.S., Doveh, S., Kim, D., Panda, R., Varol, G., Oliva A., Ordonez, V., Feris, R., & Karlinsky, L. (2023). Going Beyond Nouns With Vision & Language Models Using Synthetic Data. The 19th International Conference on Computer Vision (ICCV 2023) Paper Supplementary Material Website News

Zhong, H., Mishra, S., Kim, D., Jin, S., Panda, R., Kuehne, H., Karlinsky, L., Saligrama, V., Oliva, A., & Feris, R. (2023). Learning Human Action Recognition Representations Without Real Humans. NeurIPS 2023 Datasets and Benchmarks Paper Website Poster

Fosco, C., Jin, S., Josephs, E., & Oliva, A. (2023). Leveraging Temporal Context in Low Representational Power Regimes. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023), pp. 10693–10703 Paper Supplementary Material Website

Kim, Y., Mishra, S., Jin, S., Panda, R., Kuehne, H., Karlinsky, L., Saligrama, V., Saenko, K., Oliva, A., & Feris, R. (2022). How Transferable are Video Representations Based on Synthetic Data? Conference on Neural Information Processing Systems (NeurIPS 2022) Datasets and Benchmarks Track, 35, 35710–35723 Paper Supplementary Material News

Fosco*, C., Josephs*, E., Andonian, A., Lee, A. , Wang, X. & Oliva, A. (2022). Deepfake Caricatures: Amplifying attention to artifacts increases deepfake detection by humans and machines. arXiv:2206.00535. arXiv Paper Website

Grauman, K. et al. (2022). Ego4D: Around the World in 3,000 Hours of Egocentric Video. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), pp. 18995–19012 arXiv Paper Paper Website

Liu, A.H., Jin, S., Lai, C.J., Rouditchenko, A., Oliva, A., & Glass, J. (2022). Cross-Modal Discrete Representation Learning. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL), (Volume 1: Long Papers), 3013–3035 Paper News

Panda*, R., Chen*, C., Fan, Q., Sun, X., Saenko, K., Oliva, A., & Feris, R. (2021). AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition. International Conference on Computer Vision (ICCV 2021), (pp. 7576-7585). Paper Website

Sun, X., Panda, R., Chen, C., Oliva, A., Feris, R., & Saenko K. (2021). Dynamic Network Quantization for Efficient Video Inference. International Conference on Computer Vision (ICCV 2021), (pp. 7375-7385). Paper Website

Pan, B., Jiang, Y., Panda, R., Wang, Z., Feris, R., & Oliva, A. (2021). IA-RED²: Interpretability-Aware Redundancy Reduction for Vision Transformer. Advances in Neural Information Processing Systems (NeurIPS 2021), 34, 24898-24911 arXiv Paper Paper Website

Bau*, D., Andonian*, A., Cui, A., Park, Y., Jahanian, A., Oliva, A., & Torralba, A. (2021). Paint by Word. arXiv, 2103.10951 arXiv Paper

Monfort*, M., Jin*, S., Liu, A., Harwath, D., Feris, R., Glass, J., & Oliva, A. (2021). Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021), (pp. 14871-14881). Paper Supplementary Material Website

Chen, C., Panda, R., Ramakrishnan, K., Feris, R., Cohn, J., Oliva, A., & Fan, Q. (2021). Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021), (pp. 6165-6175). arXiv Paper

Pan, B., Panda, R., Fosco, C., Lin, C., Andonian, A., Meng, Y., Saenko, K., Oliva, A., & Feris, R. (2021). VA-RED²: Video Adaptive Redundancy Reduction. Ninth International Conference on Learning Representations (ICLR 2021). Paper Website

Meng, Y., Panda, R., Lin, C., Sattigeri, P., Karlinsky, L., Saenko, K., Oliva, A., & Feris, R. (2021). AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition. Ninth International Conference on Learning Representations (ICLR 2021). Paper Website

Bylinskii, Z., Madan, S., Tancik, M., Recasens, A., Zhong, K., Alsheikh, S., Pfister, H., Oliva, A., & Durand, F. (2021). Parsing and Summarizing Infographics with Synthetically Trained Icon Proposals. In 2021 IEEE 14th Pacific Visualization Symposium (PacificVis), (pp. 31-40). arXiv Paper Website

Monfort, M., Ramakrishnan, K., Andonian, A., McNamara, B., Lascelles, A., Pan, B., Fan, Q., Gutfreund, D., Feris, R., & Oliva, A. (2021) Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding. IEEE Pattern Analysis and Machine Intelligence (PAMI), 44(12), 9434-9445. arXiv Paper Paper Website

Newman*, A., Fosco*, C., Casser, V., Lee, A., McNamara, B., & Oliva, A. (2020). Multimodal Memorability: Modeling Effects of Semantics and Decay on Video Memorability. Proceedings of the 16th European Conference on Computer Vision (ECCV 2020) Paper Website

Andonian*, A., Fosco*, C, Monfort, M., Lee, A., Feris, R., Vondrick, C., & Oliva, A. (2020). We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos. Proceedings of the 16th European Conference on Computer Vision (ECCV 2020) arXiv Paper Website News

Meng, Y., Lin, C., Panda, R., Sattigeri, P., Karlinsky, L., Oliva, A. Saenko, K., & Feris, R. (2020). AR-Net: Adaptive Frame Resolution for Efficient Action Recognition. Proceedings of the 16th European Conference on Computer Vision (ECCV 2020) arXiv Paper Website

Fosco*, C., Newman*, A., Sukhum, P., Zhang, Y., Zhao, N., Oliva, A., & Bylinskii, Z. (2020). How much time do you have? Modeling multi-duration saliency.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020) Paper Website News

Monfort, M., Andonian, A., Zhou, B., Ramakrishnan, K., Adel Bargal, S., Yan, T., Brown, L., Fan, Q., Gutfreund, D., Vondrick, C., & Oliva, A. (2020). Moments in Time dataset: one million videos for event understanding. IEEE Pattern Analysis and Machine Intelligence (PAMI), 42(2), 502–508.Paper Website

Amini, L., Chen, C.-H., Cox, D., Oliva, A., & Torralba, A. (2020). Experiences and Insights for Collaborative Industry-Academic Research in Artificial Intelligence. AI Magazine. 41(1), 70–81. Paper

Ramakrishnan, K., Panda, R., Fan, Q., Henning, J., Oliva, A. & Feris, R. (2020). Relationship Matters: Relation Guided Knowledge Transfer for Incremental Learning of Object Detectors. IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2020), Continual Learning in Computer Vision (CLVISION) Paper

Goetschalckx*, L., Andonian*, A., Oliva, A., & Isola, P. (2019). GANalyze: Towards Visual Definition of Cognitive Image Properties. IEEE International Conference on Computer Vision (ICCV), 5744–5753 PaperWebsiteNews

Xiao, T., Fan, Q., Gutfreund, D., Monfort, M., Oliva, A., & Zhou, B. (2019). Reasoning About Human-Object Interactions Through Dual Attention Networks. IEEE International Conference on Computer Vision (ICCV), 3919–3928 Paper Website

Zhou,B., Bau, D., Oliva, A., & Torralba, A. (2019). Interpreting Deep Visual Representations via Network Dissection. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 41, 9, 2131–2145 Paper Website

Ramakrishnan*, K., Monfort*, M., McNamara, B., Lascelles, A., Gutfreund, D., Feris, R., & Oliva, A. (2019). Identifying Interpretable Action Units in Deep Networks.IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019) Workshop on Explainable AI. Paper

Monfort, M., Ramakrishnan, K., McNamara, B., Lascelles, A., Gutfreund, D., Feris, R., & Oliva, A. (2019). Examining Interpretable Feature Relationships in Deep Networks for Action recognition.ICML 2019 Workshop Deep Phenomena. Paper

Bylinskii, Z., Judd, T., Oliva, A., Torralba, A., & Durand, F. (2019). What do different evaluation metrics tell us about saliency models? IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 41(3), 740–757. Paper Website

Zhou,B., Andonian. A., Oliva, A., & Torralba, A. (2018). Temporal Relational Reasoning in Videos. European Conference on Computer Vision (ECCV)Website News

Zhou, B., Lapedriza, A., Khosla, A., Oliva, A., & Torralba, A. (2018). Places: A 10 million Image Database for Scene Recognition.IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 40(6), 1452–1464.PaperDemo Website Places CNN Models

Madan, S., Bylinskii, Z., Tancik, M., Recasens, A., Zhong, K., Alsheikh, S., Pfister, H., Oliva, A. & Durand, F. (2018). Synthetically Trained Icon Proposals for Parsing and Summarizing Infographics. arXiv, 1807.10441. arXiv Paper Website

Bau*,D., Zhou*,B., Khosla,A., Oliva, A., & Torralba, A. (2017). Network Dissection: Quantifying Interpretability of Deep Visual Representations. IEEE Computer Vision and Pattern Recognition (CVPR), pp. 2695–2702. PaperWebsite TalkVideo News

Monfort, M., Johnson, M., Oliva, A., & Hofmann, K. (2017). Asynchronous Data Aggregation for Training Visual Navigation Networks. Lifelong Learning: A Reinforcement Learning Approach Workshop at ICML, Sydney, Australia. Paper

Bylinskii, Z.*, Alsheikh, S.*, Madan, S.*, Recasens, A.*, Zhong, K., Pfister, H., Durand, F., & Oliva, A. (2017). Understanding Infographics through Textual and Visual Tag Prediction. arXiv 1709.09215 arXiv Paper

Borkin*, A.M., Bylinskii*, Z., Kim, N.W., Bainbridge, C.M., Yeh, C.S., Borkin, D., Pfister, H., & Oliva, A. (2016). Beyond Memorability: Visualization Recognition and Recall. InfoVis 2015 IEEE Transactions on Visualization and Computer Graphics, 22(1), 519–528. Paper Supplementary Material Website Video News

Zhou, B., Khosla, A., Lapedriza , A., Oliva, A., & Torralba, A. (2016). Learning Deep Features for Discriminative Localization. IEEE Conference on Computer Vision and Pattern Recogntion (CVPR), pp. 2921–2929. arXiv Paper Website

Bylinskii, Z., Recasens, A., Borji , A., Oliva, A., Torralba, A., & Durand, F. (2016). Where should saliency models look next? Proceedings of the European Conference in Computer Vision (ECCV), Amsterdam Paper Supplementary Material Poster

Khosla, A, Raju, A.S., Torralba, A., & Oliva, A. (2015). Understanding and Predicting Image Memorability at a Large Scale.IEEE International Conference on Computer Vision (ICCV), pp. 2390–2398.PaperWebsite News

Vondrick, C, Pirsiavash, H., Oliva, A., & Torralba, A. (2015). Learning Visual Biases from Human Imagination.Advances in Neural Information Processing Systems (NIPS), 28. Paper

Zhou, B., Khosla, A., Lapedriza , A., Oliva, A., & Torralba, A. (2015). Object Detectors emerge in Deep Scene CNNs .International Conference on Learning Representations (ICLR 2015). arXiv Paper Slides Visualization Places-CNN Visualization ImageNet-CNN

Zhou, B., Lapedriza , A., Xiao, J., Torralba, A., & Oliva, A. (2014). Learning Deep Features for Scene Recognition using Places Database.Conference on Neural Information Processing Systems (NIPS). Paper Website Demo

Isola, P., Xiao, J., Parikh, D, Torralba, A., & Oliva, A. (2014). What makes a photograph memorable? IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 36(7), 1469–1482. Paper

Zhou, B., Liu, L., Oliva, A., & Torralba, A. (2014). Recognizing City Identity via Attribute Analysis of Geo-tagged Images. Proceedings of the 13th European Conference on Computer Vision (ECCV). Paper

Vu, T.H., Olsson, C., Laptev, I., Oliva, A., & Sivic, J. (2014). Predicting Actions from Static Scenes. Proceedings of the 13th European Conference on Computer Vision (ECCV). PaperWebsite

Khosla, A., Bainbridge, W.A., Torralba, A., & Oliva, A. (2013). Modifying the Memorability of Face Photographs. Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp 3200–3207. Paper News Website

Borkin, M.A, Vo, A.A., Bylinskii, Z., Isola, P., Sunkavalli, S., Oliva, A., & Pfister, H. (2013). What makes a visualization memorable? IEEE Transactions on Visualization and Computer Graphics (TVCG), 19(12), 2306–2315. Paper News Website

Khosla, A., Xiao, J., Torralba, A., & Oliva, A. (2012). Memorability of Image Regions.Advances in Neural Information Processing Systems (NIPS), P. Bartlett and F.C.N. Pereira and C.J.C. Burges and L. Bottou and K.Q. Weinberge (Eds.), 25 ,305–313. Paper PosterWebsite

Khosla, A., Xiao, J., Isola, P., Torralba, A., & Oliva, A. (2012). Image memorability and visual inception. In SIGGRAPH Asia 2012 technical briefs, (pp. 1–4). Paper

Isola, P., Parikh, D., Torralba, A., & Oliva, A. (2011). Understanding the Intrinsic Memorability of Images. Advances in Neural Information Processing Systems (NIPS), J. Shawe-Taylor and R.S. Zemel and P. Bartlett and F.C.N. Pereira and K.Q. Weinberger (Eds.), 24, 2429–2437. Paper Poster Website

Isola, P., Xiao, J., Torralba, A., & Oliva, A. (2011). What makes an image memorable? Proceedings of the 24rd IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 145–152). Paper Poster Website

Xiao, J., Hayes, J., Ehinger, K., Oliva, A., & Torralba, A. (2010). SUN Database: Large-scale Scene Recognition from Abbey to Zoo. Proceedings of the 23rd IEEE Conference on Computer Vision and Pattern Recognition, (pp. 3485–3492), IEEE Computer Society. Paper Website

Ross, M.G., & Oliva, A. (2010). Estimating perception of scene layout properties from global image features. Journal of Vision, 10(1), 2-2. Website Paper

Oliva, A. & Torralba, A. (2007). The Role of Context in Object Recognition. Trends in Cognitive Sciences, 11(12), 520–527. Paper

Serre, T., Oliva, A., & Poggio, T. A. (2007). A feedforward architecture accounts for rapid categorization. Proceedings of the National Academy of Sciences, 104 (15), 6424–6429 Paper Poster Slides

Oliva, A. & Torralba, A. (2006). Building the Gist of a Scene: The Role of Global Image Features in Recognition. Progress in Brain Research: Visual perception, 155, 23–36. Paper

Hidalgo-Sotelo, B., Oliva, A., & Torralba, A. (2005). Human Learning of Contextual Priors for Object Search: Where does the time go? Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - vol. 3, p86–86.Paper

Torralba, A., & Oliva, A. (2003). Statistics of Natural Images Categories.Network: Computation in Neural Systems, 14, 391–412. Paper

Oliva, A., Torralba, A. Casthelano, M., & Henderson, J. (2003). Top-Down control of visual attention in object detection. Proceeding of the IEEE International Conference Image Processing, vol1 (pp 253–256).Paper

Torralba, A., & Oliva, A. (2002). Depth estimation from image structure. IEEE Pattern Analysis and Machine Intelligence (PAMI), 24, 1226–1238. Paper

Oliva, A., & Torralba, A. (2002). Scene-centered description from spatial envelope properties. Lecture Note in Computer Science Serie Proc. Second International Workshop on Biologically Motivated Computer Vision, Eds: H. Bulthoff, S.W. Lee, T. Poggio, & C. Wallraven. Srpinger-Verlag, Tuebingen, Germany (pp.263–272).Paper

Oliva, A., & Torralba, A. (2001). Modeling the Shape of the Scene: a Holistic Representation of the Spatial Envelope. International Journal in Computer Vision, 42, 145–175. Paper Database

Guérin-Dugué, A., & Oliva, A. (2000). Classification of scene photographs from local orientations features. Pattern Recognition Letters, 21 (13–14), 1135–1140. Paper

Torralba, A. & Oliva, A. (1999). Semantic organization of scenes using discriminant structural templates. Proceedings of the Seventh IEEE International Conference on Computer Vision, Vol. 2, pp. 1253–1258. Paper

Oliva, A., Torralba, A., Guérin-Dugué, A., & Hérault, J. (1999). Global semantic classification of scenes using power spectrum templates. In Challenge of image retrieval, pp. 1–11. Paper

Hérault, J., Oliva, A., & Guérin-Dugué, A. (1997). Scene categorisation by curvilinear component analysis of low frequency spectra. In ESANN'97: European symposium on artificial neural networks, pp. 91–96. Paper

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