141 citations · 272 across the 7 of their papers we have counts for
7 papers
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
Jun Ma, Feifei Li, Sumin Kim +79
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive co…
Taming Mambas for Voxel Level 3D Medical Image Segmentation
Luca Lumetti, Vittorio Pipoli, Kevin Marchesini +3
Recently, the field of 3D medical segmentation has been dominated by deep learning models employing Convolutional Neural Networks (CNNs) and Transformer-based architectures, each w…
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…
Recognizing and Presenting the Storytelling Video Structure with Deep Multimodal Networks
Lorenzo Baraldi, Costantino Grana, Rita Cucchiara
This paper presents a novel approach for temporal and semantic segmentation of edited videos into meaningful segments, from the point of view of the storytelling structure. The obj…
Hierarchical Boundary-Aware Neural Encoder for Video Captioning
Lorenzo Baraldi, Costantino Grana, Rita Cucchiara
The use of Recurrent Neural Networks for video captioning has recently gained a lot of attention, since they can be used both to encode the input video and to generate the correspo…
Scene-driven Retrieval in Edited Videos using Aesthetic and Semantic Deep Features
Lorenzo Baraldi, Costantino Grana, Rita Cucchiara
This paper presents a novel retrieval pipeline for video collections, which aims to retrieve the most significant parts of an edited video for a given query, and represent them wit…
A Deep Siamese Network for Scene Detection in Broadcast Videos
Lorenzo Baraldi, Costantino Grana, Rita Cucchiara
We present a model that automatically divides broadcast videos into coherent scenes by learning a distance measure between shots. Experiments are performed to demonstrate the effec…