805 citations · 1.9k across the 55 of their papers we have counts for
9 papers · 1 filter
Object Discovery in Videos as Foreground Motion Clustering
Christopher Xie, Yu Xiang, Zaid Harchaoui +1
We consider the problem of providing dense segmentation masks for object discovery in videos. We formulate the object discovery problem as foreground motion clustering, where the g…
Convolutional Patch Representations for Image Retrieval: an Unsupervised Approach
Mattis Paulin, Julien Mairal, Matthijs Douze +3
Convolutional neural networks (CNNs) have recently received a lot of attention due to their ability to model local stationary structures in natural images in a multi-scale fashion,…
Beat-Event Detection in Action Movie Franchises
Danila Potapov, Matthijs Douze, Jerome Revaud +2
While important advances were recently made towards temporally localizing and recognizing specific human actions or activities in videos, efficient detection and classification of…
DeepMatching: Hierarchical Deformable Dense Matching
Jerome Revaud, Philippe Weinzaepfel, Zaid Harchaoui +1
We introduce a novel matching algorithm, called DeepMatching, to compute dense correspondences between images. DeepMatching relies on a hierarchical, multi-layer, correlational arc…
Label-Embedding for Image Classification
Zeynep Akata, Florent Perronnin, Zaid Harchaoui +1
Attributes act as intermediate representations that enable parameter sharing between classes, a must when training data is scarce. We propose to view attribute-based image classifi…
EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow
Jerome Revaud, Philippe Weinzaepfel, Zaid Harchaoui +1
We propose a novel approach for optical flow estimation , targeted at large displacements with significant oc-clusions. It consists of two steps: i) dense matching by edge-preservi…
Convolutional Kernel Networks
Julien Mairal, Piotr Koniusz, Zaid Harchaoui +1
An important goal in visual recognition is to devise image representations that are invariant to particular transformations. In this paper, we address this goal with a new type of…
Fast and Robust Archetypal Analysis for Representation Learning
Yuansi Chen, Julien Mairal, Zaid Harchaoui
We revisit a pioneer unsupervised learning technique called archetypal analysis, which is related to successful data analysis methods such as sparse coding and non-negative matrix…
On learning to localize objects with minimal supervision
Hyun Oh Song, Ross Girshick, Stefanie Jegelka +3
Learning to localize objects with minimal supervision is an important problem in computer vision, since large fully annotated datasets are extremely costly to obtain. In this paper…