There are 7 repositories under open-set-recognition topic.
[ECCV2024] Video Foundation Models & Data for Multimodal Understanding
A curated list of papers & resources linked to open set recognition, out-of-distribution, open set domain adaptation and open world recognition
Benchmarking Generalized Out-of-Distribution Detection
The Official Repository for "Generalized OOD Detection: A Survey"
👽 Out-of-Distribution Detection with PyTorch
Open Set Recognition
Papers for Open Knowledge Discovery
Learning Placeholders for Open-Set Recognition (CVPR'21 Oral)
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.
CVPR 2019: Ranked List Loss for Deep Metric Learning, with extension for TPAMI submission
Open-source code for our paper: Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
This is the official repository for the paper "A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges".
Official code for RbA: Segmenting Unknown Regions Rejected by All (ICCV 2023)
[CVPR 2022 Oral] Towards Open Set Temporal Action Localization
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.
Official PyTorch Repository of "Difficulty-Aware Simulator for Open Set Recognition" (ECCV 2022 Paper)
[ECCV 2020] Pytorch codes for Open-set Adversarial Defense
Code release for Mind the Gap: Enlarging the Domain Gap in Open Set Domain Adaptation (TCSVT 2023)
Open-Set Recognition Using Intra-Class Splitting
A project to train your model from scratch or fine-tune a pretrained model using the losses provided in this library to improve out-of-distribution detection and uncertainty estimation performances. Calibrate your model to produce enhanced uncertainty estimations. Detect out-of-distribution data using the defined score type and threshold.
PyTorch implementation of our CVPR 2024 paper "Unified Entropy Optimization for Open-Set Test-Time Adaptation"
Official Implementation of "Few-Shot Open-Set Recognition of Hyperspectral Images with Outlier Calibration Network" (WACV22)
This is a novel unknown sar target identification method based on feature extraction networks and KLD-RPA joint discrimination. Experiment results form MSTAR dataset shows that our proposed Fea-DA achieves state of the art unknown sar target identification accuracy while maintaining the high recognition accuracy of known target.
Open set classification of car models. This 3-step classifier solves the problem where dogs are classified as cars, by first filtering these images out using ResNet CNNs transfer-trained on different datasets.
"A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?" (CVPR 2024)
Open-Set Support Vector Machines (OSSVM) [see commit message https://github.com/pedrormjunior/ossvm/commit/50d51dc482c8e13df7d9037976b97db7e60a1ccf for usage]
Official Implementation of "MORGAN: Meta-Learning-based Few-Shot Open-Set Recognition via Generative Adversarial Network" (WACV23)