665 citations · 1.3k across the 35 of their papers we have counts for
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The Group Loss for Deep Metric Learning
Ismail Elezi, Sebastiano Vascon, Alessandro Torcinovich +2
Deep metric learning has yielded impressive results in tasks such as clustering and image retrieval by leveraging neural networks to obtain highly discriminative feature embeddings…
Weakly Supervised Semantic Segmentation Using Constrained Dominant Sets
Sinem Aslan, Marcello Pelillo
The availability of large-scale data sets is an essential pre-requisite for deep learning based semantic segmentation schemes. Since obtaining pixel-level labels is extremely expen…
Dominant Set Clustering and Pooling for Multi-View 3D Object Recognition
Chu Wang, Marcello Pelillo, Kaleem Siddiqi
View based strategies for 3D object recognition have proven to be very successful. The state-of-the-art methods now achieve over 90% correct category level recognition performance…
Separating Structure from Noise in Large Graphs Using the Regularity Lemma
Marco Fiorucci, Francesco Pelosin, Marcello Pelillo
How can we separate structural information from noise in large graphs? To address this fundamental question, we propose a graph summarization approach based on Szemerédi's Regulari…
Unsupervised Domain Adaptation using Graph Transduction Games
Sebastiano Vascon, Sinem Aslan, Alessandro Torcinovich +3
Unsupervised domain adaptation (UDA) amounts to assigning class labels to the unlabeled instances of a dataset from a target domain, using labeled instances of a dataset from a rel…
Deep Constrained Dominant Sets for Person Re-identification
Leulseged Tesfaye Alemu, Marcello Pelillo, Mubarak Shah
In this work, we propose an end-to-end constrained clustering scheme to tackle the person re-identification (re-id) problem. Deep neural networks (DNN) have recently proven to be e…