20 citations · 55 across the 10 of their papers we have counts for
11 papers
A Contrastive Teacher-Student Framework for Novelty Detection under Style Shifts
Hossein Mirzaei, Mojtaba Nafez, Moein Madadi +12
There have been several efforts to improve Novelty Detection (ND) performance. However, ND methods often suffer significant performance drops under minor distribution shifts caused…
Time Does Tell: Self-Supervised Time-Tuning of Dense Image Representations
Mohammadreza Salehi, Efstratios Gavves, Cees G. M. Snoek +1
Spatially dense self-supervised learning is a rapidly growing problem domain with promising applications for unsupervised segmentation and pretraining for dense downstream tasks. D…
InForecaster: Forecasting Influenza Hemagglutinin Mutations Through the Lens of Anomaly Detection
Ali Garjani, Atoosa Malemir Chegini, Mohammadreza Salehi +6
The influenza virus hemagglutinin is an important part of the virus attachment to the host cells. The hemagglutinin proteins are one of the genetic regions of the virus with a high…
Fake It Till You Make It: Towards Accurate Near-Distribution Novelty Detection
Hossein Mirzaei, Mohammadreza Salehi, Sajjad Shahabi +4
We aim for image-based novelty detection. Despite considerable progress, existing models either fail or face a dramatic drop under the so-called "near-distribution" setting, where…
ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts
Akari Asai, Mohammadreza Salehi, Matthew E. Peters +1
This work introduces a new multi-task, parameter-efficient language model (LM) tuning method that learns to transfer knowledge across different tasks via a mixture of soft prompts-…
MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound
Rowan Zellers, Jiasen Lu, Ximing Lu +7
As humans, we navigate a multimodal world, building a holistic understanding from all our senses. We introduce MERLOT Reserve, a model that represents videos jointly over time -- t…
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges
Mohammadreza Salehi, Hossein Mirzaei, Dan Hendrycks +3
Machine learning models often encounter samples that are diverged from the training distribution. Failure to recognize an out-of-distribution (OOD) sample, and consequently assign…
Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomalies
Masoud Pourreza, Mohammadreza Salehi, Mohammad Sabokrou
Video anomaly detection has proved to be a challenging task owing to its unsupervised training procedure and high spatio-temporal complexity existing in real-world scenarios. In th…
Multiresolution Knowledge Distillation for Anomaly Detection
Mohammadreza Salehi, Niousha Sadjadi, Soroosh Baselizadeh +2
Unsupervised representation learning has proved to be a critical component of anomaly detection/localization in images. The challenges to learn such a representation are two-fold.…
Puzzle-AE: Novelty Detection in Images through Solving Puzzles
Mohammadreza Salehi, Ainaz Eftekhar, Niousha Sadjadi +2
Autoencoder, as an essential part of many anomaly detection methods, is lacking flexibility on normal data in complex datasets. U-Net is proved to be effective for this purpose but…
ARAE: Adversarially Robust Training of Autoencoders Improves Novelty Detection
Mohammadreza Salehi, Atrin Arya, Barbod Pajoum +4
Autoencoders (AE) have recently been widely employed to approach the novelty detection problem. Trained only on the normal data, the AE is expected to reconstruct the normal data e…