7 citations · 7 across the 10 of their papers we have counts for
10 papers · 1 filter
On Color Alignment in VAE Latent Spaces and Its Applications
Julian D. Santamaria, Kai Wang, Jesús Malo +2
Variational autoencoders (VAEs) are a key part of modern text-to-image models, which generate images within their latent space. VAEs are known to disentangle the main factors of va…
Human-AI Perceptual Alignment by Playing Hues and Cues
Nuria Alabau-Bosque, Jorge Vila-Tomás, Paula Daudén-Oliver +3
Evaluating the perceptual alignment between Contrastive Vision-Language Models (CVLMs) and humans is typically constrained by traditional benchmarks that overlook fine-grained sema…
Do Vision Encoders Exhibit Human-like Color Thresholds?
Engy Ehab, Pablo Hernández-Cámara, Nahla Belal +3
Understanding and characterizing human color perception is a longstanding research goal. One of the most traditional approaches is looking for the human color discrimination thresh…
Color Names in Vision-Language Models
Alexandra Gomez-Villa, Pablo Hernández-Cámara, Muhammad Atif Butt +3
Color serves as a fundamental dimension of human visual perception and a primary means of communicating about objects and scenes. As vision-language models (VLMs) become increasing…
Hues and Cues: Human vs. CLIP
Nuria Alabau-Bosque, Jorge Vila-Tomás, Paula Daudén-Oliver +4
Playing games is inherently human, and a lot of games are created to challenge different human characteristics. However, these tasks are often left out when evaluating the human-li…
From Images to Perception: Emergence of Perceptual Properties by Reconstructing Images
Pablo Hernández-Cámara, Jesus Malo, Valero Laparra
A number of scientists suggested that human visual perception may emerge from image statistics, shaping efficient neural representations in early vision. In this work, a bio-inspir…
Do Vision Transformers See Like Humans? Evaluating their Perceptual Alignment
Pablo Hernández-Cámara, Jose Manuel Jaén-Lorites, Jorge Vila-Tomás +2
Vision Transformers (ViTs) achieve remarkable performance in image recognition tasks, yet their alignment with human perception remains largely unexplored. This study systematicall…
Contrast Sensitivity in Multimodal Large Language Models: A Psychophysics-Inspired Evaluation
Pablo Hernández-Cámara, Alexandra Gomez-Villa, Jose Manuel Jaén-Lorites +3
Understanding how Multimodal Large Language Models (MLLMs) process low-level visual features is critical for evaluating their perceptual abilities and has not been systematically c…
On the dynamic evolution of CLIP texture-shape bias and its relationship to human alignment and model robustness
Pablo Hernández-Cámara, Jose Manuel Jaén-Lorites, Alexandra Gómez-Villa +3
Contrastive language-image models such as CLIP have demonstrated remarkable generalization capabilities. However, how their internal visual representations evolve during training a…
The Art of Deception: Color Visual Illusions and Diffusion Models
Alex Gomez-Villa, Kai Wang, Alejandro C. Parraga +4
Visual illusions in humans arise when interpreting out-of-distribution stimuli: if the observer is adapted to certain statistics, perception of outliers deviates from reality. Rece…