156 citations · 219 across the 12 of their papers we have counts for
13 papers
Self-Supervised Iterative Refinement for Anomaly Detection in Industrial Quality Control
Muhammad Aqeel, Shakiba Sharifi, Marco Cristani +1
This study introduces the Iterative Refinement Process (IRP), a robust anomaly detection methodology designed for high-stakes industrial quality control. The IRP enhances defect de…
Enhancing Split Computing and Early Exit Applications through Predefined Sparsity
Luigi Capogrosso, Enrico Fraccaroli, Giulio Petrozziello +4
In the past decade, Deep Neural Networks (DNNs) achieved state-of-the-art performance in a broad range of problems, spanning from object classification and action recognition to sm…
Leveraging Latent Diffusion Models for Training-Free In-Distribution Data Augmentation for Surface Defect Detection
Federico Girella, Ziyue Liu, Franco Fummi +3
Defect detection is the task of identifying defects in production samples. Usually, defect detection classifiers are trained on ground-truth data formed by normal samples (negative…
Diffusion-based Image Generation for In-distribution Data Augmentation in Surface Defect Detection
Luigi Capogrosso, Federico Girella, Francesco Taioli +5
In this study, we show that diffusion models can be used in industrial scenarios to improve the data augmentation procedure in the context of surface defect detection. In general,…
Unsupervised Active Visual Search with Monte Carlo planning under Uncertain Detections
Francesco Taioli, Francesco Giuliari, Yiming Wang +6
We propose a solution for Active Visual Search of objects in an environment, whose 2D floor map is the only known information. Our solution has three key features that make it more…
I-SPLIT: Deep Network Interpretability for Split Computing
Federico Cunico, Luigi Capogrosso, Francesco Setti +3
This work makes a substantial step in the field of split computing, i.e., how to split a deep neural network to host its early part on an embedded device and the rest on a server.…
Pose Forecasting in Industrial Human-Robot Collaboration
Alessio Sampieri, Guido D'Amely, Andrea Avogaro +5
Pushing back the frontiers of collaborative robots in industrial environments, we propose a new Separable-Sparse Graph Convolutional Network (SeS-GCN) for pose forecasting. For the…
POMP++: Pomcp-based Active Visual Search in unknown indoor environments
Francesco Giuliari, Alberto Castellini, Riccardo Berra +5
In this paper we focus on the problem of learning online an optimal policy for Active Visual Search (AVS) of objects in unknown indoor environments. We propose POMP++, a planning s…
The SARAS Endoscopic Surgeon Action Detection (ESAD) dataset: Challenges and methods
Vivek Singh Bawa, Gurkirt Singh, Francis KapingA +16
For an autonomous robotic system, monitoring surgeon actions and assisting the main surgeon during a procedure can be very challenging. The challenges come from the peculiar struct…
Forecasting People Trajectories and Head Poses by Jointly Reasoning on Tracklets and Vislets
Irtiza Hasan, Francesco Setti, Theodore Tsesmelis +5
In this work, we explore the correlation between people trajectories and their head orientations. We argue that people trajectory and head pose forecasting can be modelled as a joi…
MX-LSTM: mixing tracklets and vislets to jointly forecast trajectories and head poses
Irtiza Hasan, Francesco Setti, Theodore Tsesmelis +3
Recent approaches on trajectory forecasting use tracklets to predict the future positions of pedestrians exploiting Long Short Term Memory (LSTM) architectures. This paper shows th…
Indirect Match Highlights Detection with Deep Convolutional Neural Networks
Marco Godi, Paolo Rota, Francesco Setti
Highlights in a sport video are usually referred as actions that stimulate excitement or attract attention of the audience. A big effort is spent in designing techniques which find…
F-formation Detection: Individuating Free-standing Conversational Groups in Images
Francesco Setti, Chris Russell, Chiara Bassetti +1
Detection of groups of interacting people is a very interesting and useful task in many modern technologies, with application fields spanning from video-surveillance to social robo…