Benchmarking the next generation of never-ending learners

Our new paper, NEVIS’22: A Stream of 100 Tasks Sampled From 30 Years of Computer Vision Research, proposes a playground to study the question of efficient knowledge transfer in a controlled and reproducible setting. The Never-Ending Visual classification Stream (NEVIS’22) is a benchmark stream in addition to an evaluation protocol, a set of initial baselines, and an open-source codebase. This package provides an opportunity for researchers to explore how models can continually build on their knowledge to learn future tasks more efficiently.

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