Co Author Listing * AnchorNet: A Weakly Supervised Network to Learn Geometry-Sensitive Features for Semantic Matching
* Assessing the aesthetic quality of photographs using generic image descriptors
* Beyond Instance-Level Image Retrieval: Leveraging Captions to Learn a Global Visual Representation for Semantic Retrieval
* Capturing the Geometry of Object Categories from Video Supervision
* Category Level Object Segmentation by Combining Bag-of-Words Models with Dirichlet Processes and Random Fields
* Combining appearance models and Markov Random Fields for category level object segmentation
* Combining Visible and Near-Infrared Cues for image Categorisation
* Data-Driven Detection of Prominent Objects
* Deep Image Retrieval: Learning Global Representations for Image Search
* End-to-End Learning of Deep Visual Representations for Image Retrieval
* Extracting Structures in Image Collections for Object Recognition
* Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings
* Fisher vectors meet Neural Networks: A hybrid classification architecture
* I Have Seen Enough: Transferring Parts Across Categories
* Latent Mixture Vocabularies for Object Categorization
* Latent mixture vocabularies for object categorization and segmentation
* Learning 3D Object Categories by Looking Around Them
* Learning Color Names for Real-World Applications
* Learning Color Names from Real-World Images
* Learning the Structure of Objects from Web Supervision
* Predicting an Object Location Using a Global Image Representation
* Self-Supervised Learning of Geometrically Stable Features Through Probabilistic Introspection
* Semantic Image Segmentation Using Visible and Near-Infrared Channels
* Semi-convolutional Operators for Instance Segmentation
* Weakly Supervised Recognition of Daily Life Activities with Wearable Sensors
* What is a good evaluation measure for semantic segmentation?
Includes: Larlus, D.[Diane] Larlus, D.
26 for Larlus, D.
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