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Found 8 papers, 5 papers with code
OpenPatch: a 3D patchwork for Out-Of-Distribution detection
We advance the field by introducing OpenPatch that builds on a large pre-trained model and simply extracts from its intermediate features a set of patch representations that describe each known class.
Large Class Separation is not what you need for Relational Reasoning-based OOD Detection
We focus exactly on such a fine-tuning-free OOD detection setting.
3DOS: Towards 3D Open Set Learning -- Benchmarking and Understanding Semantic Novelty Detection on Point Clouds
In recent years there has been significant progress in the field of 3D learning on classification, detection and segmentation problems.
Semantic Novelty Detection via Relational Reasoning
We claim that a tailored representation learning strategy may be the right solution for effective and efficient semantic novelty detection.
Contrastive Learning for Cross-Domain Open World Recognition
The ability to evolve is fundamental for any valuable autonomous agent whose knowledge cannot remain limited to that injected by the manufacturer.
Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation
Vision systems trained in closed-world scenarios fail when presented with new environmental conditions, new data distributions, and novel classes at deployment time.
Rethinking Domain Generalization Baselines
Despite being very powerful in standard learning settings, deep learning models can be extremely brittle when deployed in scenarios different from those on which they were trained.
Ranked #54 on
Domain Generalization
on PACS
One-Shot Unsupervised Cross-Domain Detection
Despite impressive progress in object detection over the last years, it is still an open challenge to reliably detect objects across visual domains.
