1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2023★ 1 cited
A Metacognitive Approach to Out-of-Distribution Detection for Segmentation
Meghna Gummadi, Cassandra Kent, Karl Schmeckpeper +1
Despite outstanding semantic scene segmentation in closed-worlds, deep neural networks segment novel instances poorly, which is required for autonomous agents acting in an open wor…
cs.CV2023
EFEM: Equivariant Neural Field Expectation Maximization for 3D Object Segmentation Without Scene Supervision
Jiahui Lei, Congyue Deng, Karl Schmeckpeper +2
We introduce Equivariant Neural Field Expectation Maximization (EFEM), a simple, effective, and robust geometric algorithm that can segment objects in 3D scenes without annotations…