92 citations · 123 across the 11 of their papers we have counts for
18 papers
Granularity-aware Adaptation for Image Retrieval over Multiple Tasks
Jon Almazán, Byungsoo Ko, Geonmo Gu +2
Strong image search models can be learned for a specific domain, ie. set of labels, provided that some labeled images of that domain are available. A practical visual search model,…
Neural Feature Fusion Fields: 3D Distillation of Self-Supervised 2D Image Representations
Vadim Tschernezki, Iro Laina, Diane Larlus +1
We present Neural Feature Fusion Fields (N3F), a method that improves dense 2D image feature extractors when the latter are applied to the analysis of multiple images reconstructib…
On the Road to Online Adaptation for Semantic Image Segmentation
Riccardo Volpi, Pau de Jorge, Diane Larlus +1
We propose a new problem formulation and a corresponding evaluation framework to advance research on unsupervised domain adaptation for semantic image segmentation. The overall goa…
ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity
Ginger Delmas, Rafael Sampaio de Rezende, Gabriela Csurka +1
An intuitive way to search for images is to use queries composed of an example image and a complementary text. While the first provides rich and implicit context for the search, th…
Learning Super-Features for Image Retrieval
Philippe Weinzaepfel, Thomas Lucas, Diane Larlus +1
Methods that combine local and global features have recently shown excellent performance on multiple challenging deep image retrieval benchmarks, but their use of local features ra…
Domain Adaptation in Multi-View Embedding for Cross-Modal Video Retrieval
Jonathan Munro, Michael Wray, Diane Larlus +2
Given a gallery of uncaptioned video sequences, this paper considers the task of retrieving videos based on their relevance to an unseen text query. To compensate for the lack of a…