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Found 5 papers, 0 papers with code
Joint Generative Modeling of Scene Graphs and Images via Diffusion Models
While previous works have explored image generation conditioned on scene graphs or layouts, our task is distinctive and important as it involves generating scene graphs themselves unconditionally from noise, enabling efficient and interpretable control for image generation.
Self-Supervised Relation Alignment for Scene Graph Generation
In the auxiliary branch, relational input features are partially masked prior to message passing and predicate prediction.
Consistent Multiple Sequence Decoding
Our formulation utilizes a consistency fusion mechanism, implemented using message passing in a Graph Neural Network (GNN), to aggregate context from related decoders.
Watch, Listen and Tell: Multi-modal Weakly Supervised Dense Event Captioning
Multi-modal learning, particularly among imaging and linguistic modalities, has made amazing strides in many high-level fundamental visual understanding problems, ranging from language grounding to dense event captioning.
Time Perception Machine: Temporal Point Processes for the When, Where and What of Activity Prediction
Numerous powerful point process models have been developed to understand temporal patterns in sequential data from fields such as health-care, electronic commerce, social networks, and natural disaster forecasting.
