Continuous Object Recognition
2 papers with code • 0 benchmarks • 0 datasets
Continuous object recognition is the task of performing object recognition on a data stream and learning continuously, trying to mitigate issues such as catastrophic forgetting.
( Image credit: CORe50 dataset )
Benchmarks
These leaderboards are used to track progress in Continuous Object Recognition
Most implemented papers
CORe50: a New Dataset and Benchmark for Continuous Object Recognition
lifelong-robotic-vision/lifelong-object-recognition-challenge
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Continuous/Lifelong learning of high-dimensional data streams is a challenging research problem.
Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-Organization
Both growing networks can expand in response to novel sensory experience: the episodic memory learns fine-grained spatiotemporal representations of object instances in an unsupervised fashion while the semantic memory uses task-relevant signals to regulate structural plasticity levels and develop more compact representations from episodic experience.
