Search Results - "Philbin, James"

Deep Stereo: Learning to Predict New Views from the World's Imagery by Flynn, John, Neulander, Ivan, Philbin, James, Snavely, Noah

“…Deep networks have recently enjoyed enormous success when applied to recognition and classification problems in computer vision [22, 33], but their use in…”
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Lost in quantization: Improving particular object retrieval in large scale image databases by Philbin, James, Chum, Ondrej, Isard, Michael, Sivic, Josef, Zisserman, Andrew

“…The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these…”
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Geometric Latent Dirichlet Allocation on a Matching Graph for Large-scale Image Datasets by Philbin, James, Sivic, Josef, Zisserman, Andrew

“…Given a large-scale collection of images our aim is to efficiently associate images which contain the same entity, for example a building or object, and to…”
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FaceNet: A unified embedding for face recognition and clustering by Schroff, Florian, Kalenichenko, Dmitry, Philbin, James

“…Despite significant recent advances in the field of face recognition [10, 14, 15, 17], implementing face verification and recognition efficiently at scale…”
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Rules of the Road: Predicting Driving Behavior With a Convolutional Model of Semantic Interactions by Hong, Joey, Sapp, Benjamin, Philbin, James

“…We focus on the problem of predicting future states of entities in complex, real-world driving scenarios. Previous research has approached this problem via…”
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Five Levels of PACS Modularity: Integrating 3D and Other Advanced Visualization Tools by Wang, Kenneth C., Filice, Ross W., Philbin, James F., Siegel, Eliot L., Nagy, Paul G.

“…The current array of PACS products and 3D visualization tools presents a wide range of options for applying advanced visualization methods in clinical…”
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Learning Fine-Grained Image Similarity with Deep Ranking by Jiang Wang, Yang Song, Leung, Thomas, Rosenberg, Chuck, Jingbin Wang, Philbin, James, Bo Chen, Ying Wu

“…Learning fine-grained image similarity is a challenging task. It needs to capture between-class and within-class image differences. This paper proposes a deep…”
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Object Mining Using a Matching Graph on Very Large Image Collections by Philbin, J., Zisserman, A.

“…Automatic organization of large, unordered image collections is an extremely challenging problem with many potential applications. Often, what is required is…”
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Object retrieval with large vocabularies and fast spatial matching by Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.

“…In this paper, we present a large-scale object retrieval system. The user supplies a query object by selecting a region of a query image, and the system…”
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Experiences with VI communication for database storage by Zhou, Yuanyuan, Bilas, Angelos, Jagannathan, Suresh, Dubnicki, Cezary, Philbin, James F, Li, Kai

“…This paper examines how VI-based interconnects can be used to improve I/O path performance between a database server and the storage subsystem. We design and…”
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Multi-series DICOM: an Extension of DICOM That Stores a Whole Study in a Single Object by Ismail, Mahmoud, Philbin, James

“…Today, most medical images are stored as a set of single-frame composite Digital Imaging and Communications in Medicine (DICOM) objects that contain the four…”
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QuadroNet: Multi-Task Learning for Real-Time Semantic Depth Aware Instance Segmentation by Goel, Kratarth, Srinivasan, Praveen, Tariq, Sarah, Philbin, James

“…Vision for autonomous driving is a uniquely challenging problem: the number of tasks required for full scene understanding is large and diverse; the quality…”
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Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval by Chum, O., Philbin, J., Sivic, J., Isard, M., Zisserman, A.

“…Given a query image of an object, our objective is to retrieve all instances of that object in a large (1M+) image database. We adopt the bag-of-visual-words…”
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Fast processing of digital imaging and communications in medicine (DICOM) metadata using multiseries DICOM format by Ismail, Mahmoud, Philbin, James

“…The digital imaging and communications in medicine (DICOM) information model combines pixel data and its metadata in a single object. There are user scenarios…”
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Will the Next Generation of PACS Be Sitting on a Cloud? by Philbin, James, Prior, Fred, Nagy, Paul

“…Cloud computing has gathered significant attention from information technology (IT) vendors in providing massively scalable applications as well as highly…”
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Separation of metadata and pixel data to speed DICOM tag morphing by Ismail, Mahmoud, Philbin, James

“…The DICOM information model combines pixel data and metadata in single DICOM object. It is not possible to access the metadata separately from the pixel data…”
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Experiences with VI communication for database storage by Zhou, Yuanyuan, Bilas, Angelos, Jagannathan, Suresh, Dubnicki, Cezary, Philbin, James F., Li, Kai

“…This paper examines how VI-based interconnects can be used to improve I/O path performance between a database server and the storage subsystem. We design and…”
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Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions by Hong, Joey, Sapp, Benjamin, Philbin, James

“…The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 8454-8462 We focus on the problem of predicting future states of entities in…”
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FISHING Net: Future Inference of Semantic Heatmaps In Grids by Hendy, Noureldin, Sloan, Cooper, Tian, Feng, Duan, Pengfei, Charchut, Nick, Xie, Yuesong, Wang, Chuang, Philbin, James

“…For autonomous robots to navigate a complex environment, it is crucial to understand the surrounding scene both geometrically and semantically. Modern…”
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PlaNet - Photo Geolocation with Convolutional Neural Networks by Weyand, Tobias, Kostrikov, Ilya, Philbin, James

“…Is it possible to build a system to determine the location where a photo was taken using just its pixels? In general, the problem seems exceptionally…”
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