55 citations · 94 across the 9 of their papers we have counts for
18 papers · 1 filter
The Group Loss++: A deeper look into group loss for deep metric learning
Ismail Elezi, Jenny Seidenschwarz, Laurin Wagner +4
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…
Relaxation Labeling Meets GANs: Solving Jigsaw Puzzles with Missing Borders
Marina Khoroshiltseva, Arianna Traviglia, Marcello Pelillo +1
This paper proposes JiGAN, a GAN-based method for solving Jigsaw puzzles with eroded or missing borders. Missing borders is a common real-world situation, for example, when dealing…
LUAI Challenge 2021 on Learning to Understand Aerial Images
Gui-Song Xia, Jian Ding, Ming Qian +33
This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in a…
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…