5 papers
Pathology-Aware Adaptive Watermarking for Text-Driven Medical Image Synthesis
Chanyoung Kim, Dayun Ju, Jinyeong Kim +3
As recent text-conditioned diffusion models have enabled the generation of high-quality images, concerns over their potential misuse have also grown. This issue is critical in the…
GBT-SAM: A Parameter-Efficient Depth-Aware Model for Generalizable Brain tumour Segmentation on mp-MRI
Cecilia Diana-Albelda, Roberto Alcover-Couso, Álvaro García-Martín +2
Gliomas are aggressive brain tumors that require accurate imaging-based diagnosis, with segmentation playing a critical role in evaluating morphology and treatment decisions. Manua…
Leveraging Contrastive Learning for Semantic Segmentation with Consistent Labels Across Varying Appearances
Javier Montalvo, Roberto Alcover-Couso, Pablo Carballeira +3
This paper introduces a novel synthetic dataset that captures urban scenes under a variety of weather conditions, providing pixel-perfect, ground-truth-aligned images to facilitate…
VLMs meet UDA: Boosting Transferability of Open Vocabulary Segmentation with Unsupervised Domain Adaptation
Roberto Alcover-Couso, Marcos Escudero-Viñolo, Juan C. SanMiguel +1
Segmentation models are typically constrained by the categories defined during training. To address this, researchers have explored two independent approaches: adapting Vision-Lang…
Layer-wise Model Merging for Unsupervised Domain Adaptation in Segmentation Tasks
Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-Viñolo +1
Merging parameters of multiple models has resurfaced as an effective strategy to enhance task performance and robustness, but prior work is limited by the high costs of ensemble cr…