activity
20202026
most citedVAE-iForest: Auto-encoding Reconstruction and Isolation-based Anomalies Detecting Fallen Objects on Road Surface

3 citations · 7 across the 5 of their papers we have counts for

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cs.CV2026

SPG: Sparse-Projected Guides with Sparse Autoencoders for Zero-Shot Anomaly Detection

Tomoyasu Nanaumi, Yukino Tsuzuki, Junichi Okubo +2

We study zero-shot anomaly detection and segmentation using frozen foundation model features, where all learnable parameters are trained only on a labeled auxiliary dataset and dep…

cs.CV20223 cited

VAE-iForest: Auto-encoding Reconstruction and Isolation-based Anomalies Detecting Fallen Objects on Road Surface

Takato Yasuno, Junichiro Fujii, Riku Ogata +1

In road monitoring, it is an important issue to detect changes in the road surface at an early stage to prevent damage to third parties. The target of the falling object may be a f…

cs.CV20212 cited

One-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map

Takato Yasuno, Junichiro Fujii, Sakura Fukami

For steel product manufacturing in indoor factories, steel defect detection is important for quality control. For example, a steel sheet is extremely delicate, and must be accurate…

cs.CV20211 cited

Road Surface Translation Under Snow-covered and Semantic Segmentation for Snow Hazard Index

Takato Yasuno, Junichiro Fujii, Hiroaki Sugawara +1

In 2020, there was a record heavy snowfall owing to climate change. In reality, 2,000 vehicles were stuck on the highway for three days. Because of the freezing of the road surface…

cs.CV20211 cited

Snowy Night-to-Day Translator and Semantic Segmentation Label Similarity for Snow Hazard Indicator

Takato Yasuno, Hiroaki Sugawara, Junichiro Fujii +1

In 2021, Japan recorded more than three times as much snowfall as usual, so road user maybe come across dangerous situation. The poor visibility caused by snow triggers traffic acc…