40.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of TrentoIT265 papers
- European Centre for Theoretical Studies in Nuclear Physics and Related AreasIT190 papers
- Istituto Nazionale di Fisica Nucleare, Trento Institute for Fundamental Physics And ApplicationsIT136 papers
- Centre National de la Recherche ScientifiqueFR99 papers
- Istituto Nazionale di Fisica NucleareIT74 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR61 papers
- Istituto di Fotonica e NanotecnologieIT59 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di GenovaIT52 papers
- University of PisaIT50 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di MilanoIT46 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma IIT46 papers
- Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di FrascatiIT45 papers
44 papers · 1 filter
EHWGesture -- A dataset for multimodal understanding of clinical gestures
Gianluca Amprimo, Alberto Ancilotto, Alessandro Savino +5
Hand gesture understanding is essential for several applications in human-computer interaction, including automatic clinical assessment of hand dexterity. While deep learning has a…
Dynamic Scoring with Enhanced Semantics for Training-Free Human-Object Interaction Detection
Francesco Tonini, Lorenzo Vaquero, Alessandro Conti +2
Human-Object Interaction (HOI) detection aims to identify humans and objects within images and interpret their interactions. Existing HOI methods rely heavily on large datasets wit…
Unsupervised deep learning for semantic segmentation of multispectral LiDAR forest point clouds
Lassi Ruoppa, Oona Oinonen, Josef Taher +5
Point clouds captured with laser scanning systems from forest environments can be utilized in a wide variety of applications within forestry and plant ecology, such as the estimati…
AL-GTD: Deep Active Learning for Gaze Target Detection
Francesco Tonini, Nicola Dall'Asen, Lorenzo Vaquero +2
Gaze target detection aims at determining the image location where a person is looking. While existing studies have made significant progress in this area by regressing accurate ga…
Lost and Found: Overcoming Detector Failures in Online Multi-Object Tracking
Lorenzo Vaquero, Yihong Xu, Xavier Alameda-Pineda +2
Multi-object tracking (MOT) endeavors to precisely estimate the positions and identities of multiple objects over time. The prevailing approach, tracking-by-detection (TbD), first…
Wild Berry image dataset collected in Finnish forests and peatlands using drones
Luigi Riz, Sergio Povoli, Andrea Caraffa +13
Berry picking has long-standing traditions in Finland, yet it is challenging and can potentially be dangerous. The integration of drones equipped with advanced imaging techniques r…
Multi-tiling Neural Radiance Field (NeRF) -- Geometric Assessment on Large-scale Aerial Datasets
Ningli Xu, Rongjun Qin, Debao Huang +1
Neural Radiance Fields (NeRF) offer the potential to benefit 3D reconstruction tasks, including aerial photogrammetry. However, the scalability and accuracy of the inferred geometr…
The Unreasonable Effectiveness of Large Language-Vision Models for Source-free Video Domain Adaptation
Giacomo Zara, Alessandro Conti, Subhankar Roy +3
Source-Free Video Unsupervised Domain Adaptation (SFVUDA) task consists in adapting an action recognition model, trained on a labelled source dataset, to an unlabelled target datas…
Interactive Neural Painting
Elia Peruzzo, Willi Menapace, Vidit Goel +9
In the last few years, Neural Painting (NP) techniques became capable of producing extremely realistic artworks. This paper advances the state of the art in this emerging research…
Combining visibility analysis and deep learning for refinement of semantic 3D building models by conflict classification
Olaf Wysocki, Eleonora Grilli, Ludwig Hoegner +1
Semantic 3D building models are widely available and used in numerous applications. Such 3D building models display rich semantics but no façade openings, chiefly owing to their ae…
Promptable Game Models: Text-Guided Game Simulation via Masked Diffusion Models
Willi Menapace, Aliaksandr Siarohin, Stéphane Lathuilière +4
Neural video game simulators emerged as powerful tools to generate and edit videos. Their idea is to represent games as the evolution of an environment's state driven by the action…
Detection-aware multi-object tracking evaluation
Juan C. SanMiguel, Jorge Muñoz, Fabio Poiesi
How would you fairly evaluate two multi-object tracking algorithms (i.e. trackers), each one employing a different object detector? Detectors keep improving, thus trackers can make…
Multimodal Across Domains Gaze Target Detection
Francesco Tonini, Cigdem Beyan, Elisa Ricci
This paper addresses the gaze target detection problem in single images captured from the third-person perspective. We present a multimodal deep architecture to infer where a perso…
A Feature-space Multimodal Data Augmentation Technique for Text-video Retrieval
Alex Falcon, Giuseppe Serra, Oswald Lanz
Every hour, huge amounts of visual contents are posted on social media and user-generated content platforms. To find relevant videos by means of a natural language query, text-vide…
GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation
Cristiano Saltori, Evgeny Krivosheev, Stéphane Lathuilière +5
3D point cloud semantic segmentation is fundamental for autonomous driving. Most approaches in the literature neglect an important aspect, i.e., how to deal with domain shift when…
Relevance-based Margin for Contrastively-trained Video Retrieval Models
Alex Falcon, Swathikiran Sudhakaran, Giuseppe Serra +2
Video retrieval using natural language queries has attracted increasing interest due to its relevance in real-world applications, from intelligent access in private media galleries…
Modeling the Background for Incremental and Weakly-Supervised Semantic Segmentation
Fabio Cermelli, Massimiliano Mancini, Samuel Rota Buló +2
Deep neural networks have enabled major progresses in semantic segmentation. However, even the most advanced neural architectures suffer from important limitations. First, they are…
3d sequential image mosaicing for underwater navigation and mapping
E. Nocerino, F. Menna, B. Chemisky +1
Although fully autonomous mapping methods are becoming more and more common and reliable, still the human operator is regularly employed in many 3D surveying missions. In a number…
Click to Move: Controlling Video Generation with Sparse Motion
Pierfrancesco Ardino, Marco De Nadai, Bruno Lepri +2
This paper introduces Click to Move (C2M), a novel framework for video generation where the user can control the motion of the synthesized video through mouse clicks specifying sim…
A Better Loss for Visual-Textual Grounding
Davide Rigoni, Luciano Serafini, Alessandro Sperduti
Given a textual phrase and an image, the visual grounding problem is the task of locating the content of the image referenced by the sentence. It is a challenging task that has sev…
Learning general and distinctive 3D local deep descriptors for point cloud registration
Fabio Poiesi, Davide Boscaini
An effective 3D descriptor should be invariant to different geometric transformations, such as scale and rotation, robust to occlusions and clutter, and capable of generalising to…
Boosting Binary Masks for Multi-Domain Learning through Affine Transformations
Massimiliano Mancini, Elisa Ricci, Barbara Caputo +1
In this work, we present a new, algorithm for multi-domain learning. Given a pretrained architecture and a set of visual domains received sequentially, the goal of multi-domain lea…
Inferring Latent Domains for Unsupervised Deep Domain Adaptation
Massimiliano Mancini, Lorenzo Porzi, Samuel Rota Bulò +2
Unsupervised Domain Adaptation (UDA) refers to the problem of learning a model in a target domain where labeled data are not available by leveraging information from annotated data…
SF-UDA: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object Detection
Cristiano Saltori, Stéphane Lathuiliére, Nicu Sebe +2
3D object detectors based only on LiDAR point clouds hold the state-of-the-art on modern street-view benchmarks. However, LiDAR-based detectors poorly generalize across domains due…