O-MaMa @ EgoExo4D Correspondence Challenge: Learning Object Mask Matching between Egocentric and Exocentric Views

• URL: http://arxiv.org/abs/2506.06026v1
• Date: Fri, 06 Jun 2025 12:19:08 GMT
• Title: O-MaMa @ EgoExo4D Correspondence Challenge: Learning Object Mask Matching between Egocentric and Exocentric Views
• Authors: Lorenzo Mur-Labadia, Maria Santos-Villafranca, Alejandro Perez-Yus, Jesus Bermudez-Cameo, Ruben Martinez-Cantin, Jose J. Guerrero,
• Abstract summary: This report re-defines cross-image segmentation by treating it as a mask matching task.<n>Our method consists of: (1) A Mask-Context that pools dense DINOv2 semantic features to obtain discriminative object-level representations from FastSAM mask candidates, (2) an Ego$leftarrow$Exo Cross-Attention that fuses multi-perspective observations, and (3) a Mask Matching contrastive loss that aligns cross-view features in a shared latent space.
• Score: 41.98584849589569
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The goal of the correspondence task is to segment specific objects across different views. This technical report re-defines cross-image segmentation by treating it as a mask matching task. Our method consists of: (1) A Mask-Context Encoder that pools dense DINOv2 semantic features to obtain discriminative object-level representations from FastSAM mask candidates, (2) an Ego$\leftrightarrow$Exo Cross-Attention that fuses multi-perspective observations, (3) a Mask Matching contrastive loss that aligns cross-view features in a shared latent space, and (4) a Hard Negative Adjacent Mining strategy to encourage the model to better differentiate between nearby objects.

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