3 citations · 7 across the 8 of their papers we have counts for
10 papers
MUMINS: Metadata-conditioned Uncertainty-aware Medical Image Next-state Synthesis
Anna Oliveras, Roger Marí, Rafael Redondo +7
Forecasting anatomical changes such as tumor growth and neurodegeneration is a challenging generative vision task. Morphological evolution is subtle relative to static anatomy, hig…
Learning from Semantic Dictionaries: Discriminative Codebook Contrastive Learning for Unified Visual Representation and Generation
Imanol G. Estepa, Jesús M Rodríguez-de-Vera, Bhalaji Nagarajan +1
Discriminative and generative vision models excel in their respective domains but remain semantically misaligned, hindering progress toward unified visual learning. We introduce LE…
LAND: Lung and Nodule Diffusion for 3D Chest CT Synthesis with Anatomical Guidance
Anna Oliveras, Roger Marí, Rafael Redondo +6
This work introduces a new latent diffusion model to generate high-quality 3D chest CT scans conditioned on 3D anatomical masks. The method synthesizes volumetric images of size 25…
Conjuring Positive Pairs for Efficient Unification of Representation Learning and Image Synthesis
Imanol G. Estepa, Jesús M. Rodríguez-de-Vera, Ignacio Sarasúa +2
While representation learning and generative modeling seek to understand visual data, unifying both domains remains unexplored. Recent Unified Self-Supervised Learning (SSL) method…
Precision at Scale: Domain-Specific Datasets On-Demand
Jesús M Rodríguez-de-Vera, Imanol G Estepa, Ignacio Sarasúa +2
In the realm of self-supervised learning (SSL), conventional wisdom has gravitated towards the utility of massive, general domain datasets for pretraining robust backbones. In this…
All4One: Symbiotic Neighbour Contrastive Learning via Self-Attention and Redundancy Reduction
Imanol G. Estepa, Ignacio Sarasúa, Bhalaji Nagarajan +1
Nearest neighbour based methods have proved to be one of the most successful self-supervised learning (SSL) approaches due to their high generalization capabilities. However, their…
ELFIS: Expert Learning for Fine-grained Image Recognition Using Subsets
Pablo Villacorta, Jesús M. Rodríguez-de-Vera, Marc Bolaños +3
Fine-Grained Visual Recognition (FGVR) tackles the problem of distinguishing highly similar categories. One of the main approaches to FGVR, namely subset learning, tries to leverag…
Hyper-Spectral Imaging for Overlapping Plastic Flakes Segmentation
Guillem Martinez, Maya Aghaei, Martin Dijkstra +5
Given the hyper-spectral imaging unique potentials in grasping the polymer characteristics of different materials, it is commonly used in sorting procedures. In a practical plastic…
Deep Learning as Feature Encoding for Emotion Recognition
Bhalaji Nagarajan, V Ramana Murthy Oruganti
Deep learning is popular as an end-to-end framework extracting the prominent features and performing the classification also. In this paper, we extensively investigate deep network…
Deep Net Features for Complex Emotion Recognition
Bhalaji Nagarajan, V Ramana Murthy Oruganti
This paper investigates the influence of different acoustic features, audio-events based features and automatic speech translation based lexical features in complex emotion recogni…