About

I am a Staff Software Engineer / Tech Lead Manager @ Google Research. My current work focuses on computer vision, mainly on instance-level recognition/retrieval. I graduated with a Ph.D. from Stanford University in 2016, under the supervision of Prof. Bernd Girod. I was also a Fulbright Science & Technology Scholar and an Accel Innovation Scholar.

News

• [Jul’22] Universal Embedding Challenge launched! We welcome everyone’s participation! See also the Google AI blog post.
• [Mar’22] Instance-Level Recognition 2022 workshop accepted at ECCV’22, with new upcoming exciting challenges on universal image embeddings and language-assisted product retrieval.
• [Jan’22] Our DELF/DELG/Receptive-field papers and instance-level recognition workshop were cited in Prof. Szeliski’s new computer vision textbook version.
• [Oct’21] BMVC’21 paper: A. Iscen, A. Araujo, B. Gong and C. Schmid, “Class-Balanced Distillation for Long-Tailed Visual Recognition”.
• [Aug’21] New paper up on arXiv: Z. Kim, A. Araujo, B. Cao, C. Askew, J. Sim, M. Green, N. F. Tilla and T. Weyand, “Towards A Fairer Landmark Recognition Dataset”.
• [May’21] Instance-Level Recognition 2021 workshop accepted at ICCV’21, see landmark retrieval and recognition challenges.
• [Oct’20] I gave a keynote talk at the SUMAC workshop at ACM MM 2020, see the video recording here.
• [Sep’20] Check out our Google AI blog post featuring DELG, our open-source codebase, landmark recognition challenges and the ECCV Instance-level Recognition workshop.
• [Jul’20] ECCV’20 paper: B. Cao*, A. Araujo* and J. Sim, “Unifying Deep Local and Global Features for Image Search”.
• [Apr’20] CVPR’20 paper (oral): T. Weyand*, A. Araujo*, B. Cao and J. Sim, “Google Landmarks Dataset v2 - A Large-Scale Benchmark for Instance-Level Recognition and Retrieval”.
• [Feb’20] Instance-Level Recognition workshop accepted at ECCV’20, see landmark retrieval and recognition challenges.
• [Nov’19] Distill paper: A. Araujo, W. Norris and J. Sim, “Computing Receptive Fields of Convolutional Neural Networks”
• [Jun’19] DELF achieved 2nd place in CVPR Visual Localization challenge (Local Features track). See our slides here.
• [Jun’19] CVPR’19 paper: M. Teichmann*, A. Araujo*, M. Zhu and J. Sim, “Detect-to-Retrieve: Efficient Regional Aggregation for Image Search”. Poster here, code here.
• [Dec’18] 2nd Landmark Recognition workshop accepted at CVPR’19. Hope you can participate in the challenges: Landmark Recognition and Landmark Retrieval.
• [Mar’19] MIPR’19 paper (Best Paper Award!): J.-B. Boin, A. Araujo and B. Girod, “Recurrent Neural Networks for Person Re-identification Revisited”
• [Mar’18] Google Research blog post discussing the Google-Landmarks dataset and challenge
• [Dec’17] We are organizing the Landmark Recognition Challenge and the Landmark Retrieval Challenge, associated to the Landmark Recognition CVPR’18 workshop. Hope you can participate!
• [Oct’17] See the DELF project webpage for code and dataset.