Fine-grained visual classification (FGVC) is much more challenging than traditional
classification tasks due to the inherently subtle intra-class object variations. Recent works …

Human adaptability relies crucially on the ability to learn and merge knowledge both from
supervised and unsupervised learning: the parents point out few important concepts, but …

A jigsaw puzzle is a recreational activity that involves assembling a certain number of pieces
into a combined and well-fitting unit without creating gaps between adjacent pieces. Two …

A block scrambling-based encryption scheme is presented to enhance the security of
Encryption-then-Compression (EtC) systems with JPEG compression, which allow us to …

This paper surveys the state-of-the-art of research in patch-based synthesis. Patch-based
methods synthesize output images by copying small regions from exemplar imagery. This …

Self-supervised learning approaches leverage unlabeled samples to acquire generic
knowledge about different concepts, hence allowing for annotation-efficient downstream …

Reassembly tasks play a fundamental role in many fields and multiple approaches exist to
solve specific reassembly problems. In this context we posit that a general unified model can …

This paper introduces new types of square-piece jigsaw puzzles: those for which the
orientation of each jigsaw piece is unknown. We propose a tree-based reassembly that …

Joint matching over a collection of objects aims at aggregating information from a large
collection of similar instances (eg images, graphs, shapes) to improve maps between pairs …

Data-driven methods serve an increasingly important role in discovering geometric,
structural, and semantic relationships between shapes. In contrast to traditional approaches …