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Found 6 papers, 2 papers with code
ESC: Evolutionary Stitched Camera Calibration in the Wild
This work introduces a novel end-to-end approach for estimating extrinsic parameters of cameras in multi-camera setups on real-life sports fields.
Divide and not forget: Ensemble of selectively trained experts in Continual Learning
Class-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know.
Generalized Continual Category Discovery
However, these settings are not well aligned with real-life scenarios, where a learning agent has access to a vast amount of unlabeled data encompassing both novel (entirely unlabeled) classes and examples from known classes.
Active Visual Exploration Based on Attention-Map Entropy
Active visual exploration addresses the issue of limited sensor capabilities in real-world scenarios, where successive observations are actively chosen based on the environment.
Sports Camera Pose Refinement Using an Evolution Strategy
This paper presents a robust end-to-end method for sports cameras extrinsic parameters optimization using a novel evolution strategy.
Reinforcement Learning for on-line Sequence Transformation
A number of problems in the processing of sound and natural language, as well as in other areas, can be reduced to simultaneously reading an input sequence and writing an output sequence of generally different length.
