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Found 4 papers, 4 papers with code
Towards Balanced Alignment: Modal-Enhanced Semantic Modeling for Video Moment Retrieval
In this paper, we introduce Modal-Enhanced Semantic Modeling (MESM), a novel framework for more balanced alignment through enhancing features at two levels.
CARIS: Context-Augmented Referring Image Segmentation
Technically, CARIS develops a context-aware mask decoder with sequential bidirectional cross-modal attention to integrate the linguistic features with visual context, which are then aligned with pixel-wise visual features.
Learning Orthogonal Prototypes for Generalized Few-Shot Semantic Segmentation
POP builds a set of orthogonal prototypes, each of which represents a semantic class, and makes the prediction for each class separately based on the features projected onto its prototype.
Partial Class Activation Attention for Semantic Segmentation
Current attention-based methods for semantic segmentation mainly model pixel relation through pairwise affinity and coarse segmentation.
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