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Found 4 papers, 0 papers with code
Human Activity Recognition in an Open World
Managing novelty in perception-based human activity recognition (HAR) is critical in realistic settings to improve task performance over time and ensure solution generalization outside of prior seen samples.
Reconstructing Humpty Dumpty: Multi-feature Graph Autoencoder for Open Set Action Recognition
Our approach uses the reconstruction error to determine the novelty of the video since unknown classes are harder to put back together and thus have a higher reconstruction error than videos from known classes.
Vector Learning for Cross Domain Representations
We leverage a sequence-to-sequence model to generate synthetic captions that have the same meaning for having a robust image generation.
Semantically Invariant Text-to-Image Generation
Along with MMVR, we propose two improvements to the text conditioned image generation.
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