[ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond
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Updated
Jan 26, 2023 - Python
[ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond
A project to add scalable state-of-the-art out-of-distribution detection (open set recognition) support by changing two lines of code! Perform efficient inferences (i.e., do not increase inference time) and detection without classification accuracy drop, hyperparameter tuning, or collecting additional data.
💠 Essential object oriented design (python, pytest, travisCI)
The Official Implementation of the ICCV-2021 Paper: Semantically Coherent Out-of-Distribution Detection.
A Python wrapper for Affinity (CRM platform).
A project to improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in your project! Perform efficient inferences (i.e., do not increase inference time) without repetitive model training, hyperparameter tuning, or collecting additional data.
Reproducing experimental results of OOD-by-MCD [Yu and Aizawa et al. ICCV 2019]
Repository for the paper "Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey"
We leverage 14 datasets as OOD test data and conduct evaluations on 8 NLU tasks over 21 popularly used models. Our findings confirm that the OOD accuracy in NLP tasks needs to be paid more attention to since the significant performance decay compared to ID accuracy has been found in all settings.
Realisitic Out-of-Distribution (OOD) Detection
[ICLR 2024 Spotlight] "Negative Label Guided OOD Detection with Pretrained Vision-Language Models"
Multilabel Out-of-Distribution Detection
A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures
splitwise system low level design for machine coding round
OOP Python code to execute sql query and generate a report
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