2 citations · 6 across the 45 of their papers we have counts for
18 papers · 1 filter
Perceive, Query & Reason: Enhancing Video QA with Question-Guided Temporal Queries
Roberto Amoroso, Gengyuan Zhang, Rajat Koner +3
Video Question Answering (Video QA) is a challenging video understanding task that requires models to comprehend entire videos, identify the most relevant information based on cont…
Personalizing Multimodal Large Language Models for Image Captioning: An Experimental Analysis
Davide Bucciarelli, Nicholas Moratelli, Marcella Cornia +2
The task of image captioning demands an algorithm to generate natural language descriptions of visual inputs. Recent advancements have seen a convergence between image captioning r…
Causal Graphical Models for Vision-Language Compositional Understanding
Fiorenzo Parascandolo, Nicholas Moratelli, Enver Sangineto +2
Recent work has empirically shown that Vision-Language Models (VLMs) struggle to fully understand the compositional properties of the human language, usually modeling an image capt…
Maximally Separated Active Learning
Tejaswi Kasarla, Abhishek Jha, Faye Tervoort +2
Active Learning aims to optimize performance while minimizing annotation costs by selecting the most informative samples from an unlabelled pool. Traditional uncertainty sampling o…
Talking to DINO: Bridging Self-Supervised Vision Backbones with Language for Open-Vocabulary Segmentation
Luca Barsellotti, Lorenzo Bianchi, Nicola Messina +5
Open-Vocabulary Segmentation (OVS) aims at segmenting images from free-form textual concepts without predefined training classes. While existing vision-language models such as CLIP…
Augmenting Multimodal LLMs with Self-Reflective Tokens for Knowledge-based Visual Question Answering
Federico Cocchi, Nicholas Moratelli, Marcella Cornia +2
Multimodal LLMs (MLLMs) are the natural extension of large language models to handle multimodal inputs, combining text and image data. They have recently garnered attention due to…
TPP-Gaze: Modelling Gaze Dynamics in Space and Time with Neural Temporal Point Processes
Alessandro D'Amelio, Giuseppe Cartella, Vittorio Cuculo +4
Attention guides our gaze to fixate the proper location of the scene and holds it in that location for the deserved amount of time given current processing demands, before shifting…
Personalized Instance-based Navigation Toward User-Specific Objects in Realistic Environments
Luca Barsellotti, Roberto Bigazzi, Marcella Cornia +2
In the last years, the research interest in visual navigation towards objects in indoor environments has grown significantly. This growth can be attributed to the recent availabili…
Positive-Augmented Contrastive Learning for Vision-and-Language Evaluation and Training
Sara Sarto, Nicholas Moratelli, Marcella Cornia +2
Despite significant advancements in caption generation, existing evaluation metrics often fail to capture the full quality or fine-grained details of captions. This is mainly due t…
Optimizing Resource Consumption in Diffusion Models through Hallucination Early Detection
Federico Betti, Lorenzo Baraldi, Rita Cucchiara +1
Diffusion models have significantly advanced generative AI, but they encounter difficulties when generating complex combinations of multiple objects. As the final result heavily de…
Fluent and Accurate Image Captioning with a Self-Trained Reward Model
Nicholas Moratelli, Marcella Cornia, Lorenzo Baraldi +1
Fine-tuning image captioning models with hand-crafted rewards like the CIDEr metric has been a classical strategy for promoting caption quality at the sequence level. This approach…
Merging and Splitting Diffusion Paths for Semantically Coherent Panoramas
Fabio Quattrini, Vittorio Pippi, Silvia Cascianelli +1
Diffusion models have become the State-of-the-Art for text-to-image generation, and increasing research effort has been dedicated to adapting the inference process of pretrained di…
μgat: Improving Single-Page Document Parsing by Providing Multi-Page Context
Fabio Quattrini, Carmine Zaccagnino, Silvia Cascianelli +2
Regesta are catalogs of summaries of other documents and, in some cases, are the only source of information about the content of such full-length documents. For this reason, they a…
Alfie: Democratising RGBA Image Generation With No $$$
Fabio Quattrini, Vittorio Pippi, Silvia Cascianelli +1
Designs and artworks are ubiquitous across various creative fields, requiring graphic design skills and dedicated software to create compositions that include many graphical elemen…
Revisiting Image Captioning Training Paradigm via Direct CLIP-based Optimization
Nicholas Moratelli, Davide Caffagni, Marcella Cornia +2
The conventional training approach for image captioning involves pre-training a network using teacher forcing and subsequent fine-tuning with Self-Critical Sequence Training to max…
Bringing Masked Autoencoders Explicit Contrastive Properties for Point Cloud Self-Supervised Learning
Bin Ren, Guofeng Mei, Danda Pani Paudel +6
Contrastive learning (CL) for Vision Transformers (ViTs) in image domains has achieved performance comparable to CL for traditional convolutional backbones. However, in 3D point cl…
Sharing Key Semantics in Transformer Makes Efficient Image Restoration
Bin Ren, Yawei Li, Jingyun Liang +6
Image Restoration (IR), a classic low-level vision task, has witnessed significant advancements through deep models that effectively model global information. Notably, the emergenc…
Binarizing Documents by Leveraging both Space and Frequency
Fabio Quattrini, Vittorio Pippi, Silvia Cascianelli +1
Document Image Binarization is a well-known problem in Document Analysis and Computer Vision, although it is far from being solved. One of the main challenges of this task is that…