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Novelty Detection

ECCV

  • incDFM: Incremental Deep Feature Modeling for Continual Novelty Detection (ECCV 2022) [Paper]
    Datasets: 1.CIFAR-10 (10 classes), 2. CIFAR-100 (super-classlevel, 20 classes), 3. EMNIST (26 classes) and 4. iNaturalist21 (phylumlevel, 9 classes)
    Task: Image Classification

WACV

  • One-Class Learned Encoder-Decoder Network With Adversarial Context Masking for Novelty Detection (WACV 2022) [Paper] [Code]
    Datasets: MNIST, CIFAR-10, UCSD
    Task: Novelty Detection, Anomaly

2021 Papers

CVPR

  • Learning Deep Classifiers Consistent With Fine-Grained Novelty Detection (CVPR 2021) [Paper]
    Datasets: small- and large-scale FGVC
    Task: Novelty Detection

AAAI

  • A Unifying Framework for Formal Theories of Novelty:Framework, Examples and Discussion (AAAI 2021) [Paper]

BMVC

  • Multi-Class Novelty Detection with Generated Hard Novel Features (BMVC 2021) [Paper]
    Datasets: Stanford Dogs, Caltech 256, CUB 200, FounderType-200
    Task: Image Classification

Older Papers

  • Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents (NeurIPS 2018) [Paper]
    Datasets: OpenAI Gym
    Task: Reinforcement Learning

  • Multivariate Triangular Quantile Maps for Novelty Detection (NeurIPS 2019) [Paper] [Code]
    Datasets: MNIST and Fashion-MNIST, KDDCUP and Thyroid
    Task: Image Classification

  • Multi-class Novelty Detection Using Mix-up Technique (WACV 2020) [Paper]
    Datasets: Caltech 256 and Stanford Dogs
    Task: Image Classification

  • Hierarchical Novelty Detection for Visual Object Recognition (CVPR 2018) [Paper]
    Datasets: ImageNet, AwA2, CUB
    Task: Image Classification

  • Adversarially Learned One-Class Classifier for Novelty Detection (CVPR 2018) [Paper]
    Datasets: MNIST, Caltech-256, UCSD Ped2
    Task: Image Classification, Anomaly Detection

  • Multiple Class Novelty Detection Under Data Distribution Shift (ECCV 2020) [Paper]
    Datasets: SVHN, MNIST and USPS, Office-31
    Task: Image Classification

  • Utilizing Patch-level Category Activation Patterns for Multiple Class Novelty Detection (ECCV 2020) [Paper]
    Datasets: Caltech256, CUB-200, Stanford Dogs and FounderType-200
    Task: Image Classification

  • Unsupervised and Semi-supervised Novelty Detection using Variational Autoencoders in Opportunistic Science Missions (BMVC 2020) [Paper]
    Datasets: Mars novelty detection Mastcam labeled dataset
    Task: Image Classification

  • Where's Wally Now? Deep Generative and Discriminative Embeddings for Novelty Detection (CVPR 2019) [Paper]
    Datasets: CIFAR-10, IN-125
    Task: Image Classification

  • Deep Transfer Learning for Multiple Class Novelty Detection (CVPR 2019) [Paper]
    Datasets: Caltech256, Caltech-UCSD Birds 200 (CUB 200), Stanford Dogs, FounderType-200
    Task: Image Classification

  • Latent Space Autoregression for Novelty Detection (CVPR 2019) [Paper] [Code]
    Datasets: MNIST, CIFAR10, UCSD Ped2 and ShanghaiTech
    Task: Image Classification, Video Anomaly Detection

  • OCGAN: One-Class Novelty Detection Using GANs With Constrained Latent Representations (CVPR 2019) [Paper] [Code]
    Datasets: COIL100, fMNIST, MNIST, CIFAR10
    Task: Image Classification

  • RaPP: Novelty Detection with Reconstruction along Projection Pathway (ICLR 2020) [Paper] [Code]
    Datasets: fMNIST, MNIST, MI-F and MI-V, STL, OTTO, SNSR, EOPT, NASA, RARM
    Task: Image Classification, Anomaly Detection

  • Novelty Detection Via Blurring (ICLR 2020) [Paper]
    Datasets: CIFAR-10, CIFAR-100, CelebA, ImageNet, LSUN, SVHN
    Task: Image Classification