1.2k citations · 2k across the 56 of their papers we have counts for
6 papers · 1 filter
Visualizing and Understanding Deep Texture Representations
Tsung-Yu Lin, Subhransu Maji
A number of recent approaches have used deep convolutional neural networks (CNNs) to build texture representations. Nevertheless, it is still unclear how these models represent tex…
Deep filter banks for texture recognition, description, and segmentation
Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos +1
Visual textures have played a key role in image understanding because they convey important semantics of images, and because texture representations that pool local image descripto…
One-to-many face recognition with bilinear CNNs
Aruni RoyChowdhury, Tsung-Yu Lin, Subhransu Maji +1
The recent explosive growth in convolutional neural network (CNN) research has produced a variety of new architectures for deep learning. One intriguing new architecture is the bil…
Multi-view Convolutional Neural Networks for 3D Shape Recognition
Hang Su, Subhransu Maji, Evangelos Kalogerakis +1
A longstanding question in computer vision concerns the representation of 3D shapes for recognition: should 3D shapes be represented with descriptors operating on their native 3D f…
Bilinear CNNs for Fine-grained Visual Recognition
Tsung-Yu Lin, Aruni RoyChowdhury, Subhransu Maji
We present a simple and effective architecture for fine-grained visual recognition called Bilinear Convolutional Neural Networks (B-CNNs). These networks represent an image as a po…
Jointly Learning Multiple Measures of Similarities from Triplet Comparisons
Liwen Zhang, Subhransu Maji, Ryota Tomioka
Similarity between objects is multi-faceted and it can be easier for human annotators to measure it when the focus is on a specific aspect. We consider the problem of mapping objec…