11 citations · 26 across the 21 of their papers we have counts for
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cs.LG2024★ 1 cited
LCA-on-the-Line: Benchmarking Out-of-Distribution Generalization with Class Taxonomies
Jia Shi, Gautam Gare, Jinjin Tian +6
We tackle the challenge of predicting models' Out-of-Distribution (OOD) performance using in-distribution (ID) measurements without requiring OOD data. Existing evaluations with "E…
cs.CV2024
Better Call SAL: Towards Learning to Segment Anything in Lidar
Aljoša Ošep, Tim Meinhardt, Francesco Ferroni +3
We propose the SAL (Segment Anything in Lidar) method consisting of a text-promptable zero-shot model for segmenting and classifying any object in Lidar, and a pseudo-labeling engi…