WebNov 22, 2024 · We show that this approach can be adapted for simultaneous semantic segmentation and dense outlier detection. We present image classification experiments on CIFAR-10, as well as semantic segmentation experiments on three existing datasets (StreetHazards, WD-Pascal, Fishyscapes Lost & Found), and one contributed dataset. WebSuch a straightforward approach achieves a new state-of-the-art performance on the publicly available Fishyscapes Lost & Found leaderboard with a large margin. Our code is publicly available at this link. Related Material @InProceedings{Jung_2024_ICCV, author = {Jung, Sanghun and Lee, Jungsoo and Gwak, Daehoon and Choi, Sungha and Choo, …

The Fishyscapes Benchmark: Measuring Blind Spots in …

WebDeep learning has enabled impressive progress in the accuracy of semantic segmentation. Yet, the ability to estimate uncertainty and detect anomalies is key for safety-critical applications like autonomous driving. Existing uncertainty estimates have mostly been evaluated on simple tasks, and it is unclear whether these methods generalize to more … WebOct 1, 2024 · This work presents a method for obtaining uncertainty scores from pixel-wise loss gradients which can be computed efficiently during inference, and shows superior performance in terms of OoD segmentation to comparable baselines on the SegmentMeIfYouCan benchmark, clearly outperforming methods which are similarly … how to remove feathers from chicken wings

Anomaly Segmentation Using Class-aware Erosion and Smoothing

WebThe proposed JSR-Net was evaluated on four datasets, Lost-and-found, Road Anomaly, Road Obstacles, and FishyScapes, achieving state-of-art performance on all, reducing the false positives significantly, while typically having the highest average precision for wide range of operation points. Related Material [ pdf ] [ bibtex ] WebOct 23, 2024 · Fishyscapes is a high-resolution dataset for anomaly estimation in semantic segmentation for urban driving scenes. The benchmark has an online testing set that is entirely unknown to the methods. ... Pinggera, P., Ramos, S., Gehrig, S., Franke, U., Rother, C., Mester, R.: Lost and found: detecting small road hazards for self-driving vehicles ... WebThe proposed JSR-Net was evaluated on four datasets, Lost-and-found, Road Anomaly, Road Obstacles, and FishyScapes, achieving state-of-art performance on all, reducing … how to remove federal judge