Long-tailed segmentation
Web22 de fev. de 2024 · Motivated by these insights, we propose a simple and scalable framework FreeSeg for extracting and leveraging these "free" object foreground … Web5 de abr. de 2024 · In this paper, we study the problem of class imbalance in semantic segmentation. We first investigate and identify the main challenges of addressing this issue through pixel rebalance. Then a simple and yet effective region rebalance scheme is derived based on our analysis.
Long-tailed segmentation
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WebInstance segmentation has witnessed a remarkable progress on class-balanced benchmarks. However, they fail to perform as accurately in real-world scenarios, where the category distribution of objects naturally comes with a long tail. Instances of head classes dominate a long-tailed dataset and they serve as negative samples of tail categories. Weblong-tailed training datasets often underperforms on a class-balanced test dataset. As datasets are scaling up nowadays, the long-tailed nature poses critical difficulties to many vision tasks, e.g., visual recognition and instance segmentation. An intuitive solution to long-tailed task is to re-balance the data distribution. Most state-of-the-art
WebDespite the previous success of object analysis, detecting and segmenting a large number of object categories with a long-tailed data distribution remains a challenging problem and is less investigated. For a large-vocabulary classifier, the chance of obtaining noisy logits is much higher, which can easily lead to a wrong recognition. WebCVF Open Access
WebRecent methods for long-tailed instance segmentation still struggle on rare object classes with few training data. We propose a simple yet effective method, Feature Augmentation … Web5 de abr. de 2024 · Region Rebalance for Long-Tailed Semantic Segmentation. In this paper, we study the problem of class imbalance in semantic segmentation. We first …
Web22 de jul. de 2024 · To address this, we develop a Gumbel Optimized Loss (GOL), for long-tailed detection and segmentation. It aligns with the Gumbel distribution of rare classes in imbalanced datasets, considering the fact that most classes in long-tailed detection have low expected probability. The proposed GOL significantly outperforms the best state-of …
Web22 de jul. de 2024 · To address this, we develop a Gumbel Optimized Loss (GOL), for long-tailed detection and segmentation. It aligns with the Gumbel distribution of rare classes … gina proia glastonbury ct facebookWebAwesome Long-Tailed Learning. We released Deep Long-Tailed Learning: A Survey and our codebase to the community. In this survey, we reviewed recent advances in long … gina presbyterian churchWebCross-Level Semantic Segmentation Guided Feature Space Decoupling And Augmentation for Fine-Grained Ship Detection Abstract: Fine-grained ship detection in optical remote sensing images is a challenging problem due to its long-tailed distributed dataset, which is often coupled with the multi-scale of ship and complex environment. gina powers mcalester