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    Chapter and Conference Paper

    Single-Stream Multi-level Alignment for Vision-Language Pretraining

    Self-supervised vision-language pretraining from pure images and text with a contrastive loss is effective, but ignores fine-grained alignment due to a dual-stream architecture that aligns image and text repre...

    Zaid Khan, B. G. Vijay Kumar, **ang Yu, Samuel Schulter in Computer Vision – ECCV 2022 (2022)

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    Chapter and Conference Paper

    Improving Face Recognition by Clustering Unlabeled Faces in the Wild

    While deep face recognition has benefited significantly from large-scale labeled data, current research is focused on leveraging unlabeled data to further boost performance, reducing the cost of human annotati...

    Aruni RoyChowdhury, **ang Yu, Kihyuk Sohn in Computer Vision – ECCV 2020 (2020)

  3. Chapter and Conference Paper

    Learning to Look around Objects for Top-View Representations of Outdoor Scenes

    Given a single RGB image of a complex outdoor road scene in the perspective view, we address the novel problem of estimating an occlusion-reasoned semantic scene layout in the top-view. This challenging proble...

    Samuel Schulter, Menghua Zhai, Nathan Jacobs in Computer Vision – ECCV 2018 (2018)

  4. Chapter and Conference Paper

    Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences

    Interest point descriptors have fueled progress on almost every problem in computer vision. Recent advances in deep neural networks have enabled task-specific learned descriptors that outperform hand-crafted d...

    Mohammed E. Fathy, Quoc-Huy Tran, M. Zeeshan Zia in Computer Vision – ECCV 2018 (2018)

  5. Chapter and Conference Paper

    Deep Deformation Network for Object Landmark Localization

    We propose a novel cascaded framework, namely deep deformation network (DDN), for localizing landmarks in non-rigid objects. The hallmarks of DDN are its incorporation of geometric constraints within a convolu...

    **ang Yu, Feng Zhou, Manmohan Chandraker in Computer Vision – ECCV 2016 (2016)

  6. Chapter and Conference Paper

    A 4D Light-Field Dataset and CNN Architectures for Material Recognition

    We introduce a new light-field dataset of materials, and take advantage of the recent success of deep learning to perform material recognition on the 4D light-field. Our dataset contains 12 material categories...

    Ting-Chun Wang, Jun-Yan Zhu, Ebi Hiroaki in Computer Vision – ECCV 2016 (2016)

  7. Chapter and Conference Paper

    On Shape and Material Recovery from Motion

    We present a framework for the joint recovery of the shape and reflectance of an object with dichromatic BRDF, using motion cues. We show that four (small or differential) motions of the object, or three motio...

    Manmohan Chandraker in Computer Vision – ECCV 2014 (2014)

  8. Chapter and Conference Paper

    A Dual Theory of Inverse and Forward Light Transport

    Inverse light transport seeks to undo global illumination effects, such as interreflections, that pervade images of most scenes. This paper presents the theoretical and computational foundations for inverse li...

    Jiamin Bai, Manmohan Chandraker, Tian-Tsong Ng in Computer Vision – ECCV 2010 (2010)