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Found 5 papers, 1 papers with code
Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation
To overcome this limitation, we introduce a contrastive representation learning framework that focuses on motion pattern for temporal scene graph generation.
Multi-Scale Contrastive Learning for Video Temporal Grounding
To resolve this problem, we propose a contrastive learning framework to capture salient semantics among video moments.
Encoding and Controlling Global Semantics for Long-form Video Question Answering
Seeking answers effectively for long videos is essential to build video question answering (videoQA) systems.
Topic Modeling as Multi-Objective Contrastive Optimization
Secondly, we explicitly cast contrastive topic modeling as a gradient-based multi-objective optimization problem, with the goal of achieving a Pareto stationary solution that balances the trade-off between the ELBO and the contrastive objective.
Grounding Language Representation with Visual Object Information via Cross Modal Pretraining
However, this approach has two main drawbacks: (i) the whole image usually contains more objects and backgrounds than the sentence itself; thus, matching them together will confuse the grounded model; (ii) CNN only extracts the features of the image but not the relationship between objects inside that, limiting the grounded model to learn complicated contexts.
