9 papers
Resonant Brane Splatting for Arbitrary-Scale Super-Resolution
Giulio Federico, Giuseppe Amato, Claudio Gennaro +2
Arbitrary-Scale Super-Resolution (ASR) reconstructs images at continuous magnification factors. Recent methods accelerate inference by replacing computationally heavy implicit neur…
Learning to Adaptively Allocate Gaussians for Arbitrary-Scale Image Super-Resolution
Giulio Federico, Giuseppe Amato, Claudio Gennaro +2
In computer graphics, visual content is continuously warped, zoomed and resampled. This occurs when engines upscale frames, users zoom into 3D scenes, or foveated VR applies varyin…
One Patch to Caption Them All: A Unified Zero-Shot Captioning Framework
Lorenzo Bianchi, Giacomo Pacini, Fabio Carrara +3
Zero-shot captioners are recently proposed models that utilize common-space vision-language representations to caption images without relying on paired image-text data. To caption…
Reviving ConvNeXt for Efficient Convolutional Diffusion Models
Taesung Kwon, Lorenzo Bianchi, Lennart Wittke +5
Recent diffusion models increasingly favor Transformer backbones, motivated by the remarkable scalability of fully attentional architectures. Yet the locality bias, parameter effic…
Learning Egocentric In-Hand Object Segmentation through Weak Supervision from Human Narrations
Nicola Messina, Rosario Leonardi, Luca Ciampi +4
Pixel-level recognition of objects manipulated by the user from egocentric images enables key applications spanning assistive technologies, industrial safety, and activity monitori…
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…