3 citations · 7 across the 7 of their papers we have counts for
7 papers
Solving Jigsaw Puzzles in the Wild: Human-Guided Reconstruction of Cultural Heritage Fragments
Omidreza Safaei, Sinem Aslan, Sebastiano Vascon +3
Reassembling real-world archaeological artifacts from fragmented pieces poses significant challenges due to erosion, missing regions, irregular shapes, and large-scale ambiguity. T…
Machine-learned global glacier ice volumes
N. Maffezzoli, E. Rignot, C. Barbante +3
We present a global dataset of glacier ice thickness modeled with IceBoost v2.0, a machine learning model trained on 7 million ice thickness measurements and informed by physical a…
ECAM: A Contrastive Learning Approach to Avoid Environmental Collision in Trajectory Forecasting
Giacomo Rosin, Muhammad Rameez Ur Rahman, Sebastiano Vascon
Human trajectory forecasting is crucial in applications such as autonomous driving, robotics and surveillance. Accurate forecasting requires models to consider various factors, inc…
Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving
Theodore Tsesmelis, Luca Palmieri, Marina Khoroshiltseva +20
This paper proposes the RePAIR dataset that represents a challenging benchmark to test modern computational and data driven methods for puzzle-solving and reassembly tasks. Our dat…
Nash Meets Wertheimer: Using Good Continuation in Jigsaw Puzzles
Marina Khoroshiltseva, Luca Palmieri, Sinem Aslan +2
Jigsaw puzzle solving is a challenging task for computer vision since it requires high-level spatial and semantic reasoning. To solve the problem, existing approaches invariably us…
OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair Navigation
Muhammad Rameez ur Rahman, Piero Simonetto, Anna Polato +3
Open vocabulary 3D object detection (OV3D) allows precise and extensible object recognition crucial for adapting to diverse environments encountered in assistive robotics. This pap…
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
Antonio Emanuele Cinà, Kathrin Grosse, Sebastiano Vascon +4
Backdoor attacks inject poisoning samples during training, with the goal of forcing a machine learning model to output an attacker-chosen class when presented a specific trigger at…