From the 1 of 52 linked papers with an AI index.
840 citations · 2.7k across the 42 of their papers we have counts for
8 papers · 1 filter
Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration
Bruno Lecouat, Jean Ponce, Julien Mairal
Non-local self-similarity and sparsity principles have proven to be powerful priors for natural image modeling. We propose a novel differentiable relaxation of joint sparsity that…
Learning Semantic Correspondence Exploiting an Object-level Prior
Junghyup Lee, Dohyung Kim, Wonkyung Lee +2
We address the problem of semantic correspondence, that is, establishing a dense flow field between images depicting different instances of the same object or scene category. We pr…
Deformable Kernel Networks for Joint Image Filtering
Beomjun Kim, Jean Ponce, Bumsub Ham
Joint image filters are used to transfer structural details from a guidance picture used as a prior to a target image, in tasks such as enhancing spatial resolution and suppressing…
SPair-71k: A Large-scale Benchmark for Semantic Correspondence
Juhong Min, Jongmin Lee, Jean Ponce +1
Establishing visual correspondences under large intra-class variations, which is often referred to as semantic correspondence or semantic matching, remains a challenging problem in…
Hyperpixel Flow: Semantic Correspondence with Multi-layer Neural Features
Juhong Min, Jongmin Lee, Jean Ponce +1
Establishing visual correspondences under large intra-class variations requires analyzing images at different levels, from features linked to semantics and context to local pattern…
Unsupervised Image Matching and Object Discovery as Optimization
Huy V. Vo, Francis Bach, Minsu Cho +4
The paper reformulates unsupervised object category discovery and image matching as a formal optimization problem and demonstrates its effectiveness on benchmark datasets.