Long-tailed visual recognition
WebTowards Visual Recognition in the Wild: Long-Tailed Sources and Open Compound Targets Web6 de mai. de 2024 · Label distributions in real-world are oftentimes long-tailed and imbalanced, resulting in biased models towards dominant labels. While long-tailed …
Long-tailed visual recognition
Did you know?
Webmance in long-tailed visual recognition on various tar-get label distributions. 2. Related work 2.1. Longtailed visual recognition Most long-tailed visual recognition methods can be di-vided into two strategies: modifying the data sampler to balance the class frequency during optimization [7, 21, 25, 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
Web16 de mai. de 2024 · In this paper, we tackle the long-tailed visual recognition problem from the categorical prototype perspective by proposing a prototype-based classifier … WebIn addition, we introduce Balanced Meta-Softmax, applying a complementary Meta Sampler to estimate the optimal class sample rate and further improve long-tailed learning. In our experiments, we demonstrate that Balanced Meta-Softmax outperforms state-of-the-art long-tailed classification solutions on both visual recognition and instance ...
Webapproach to long-tailed visual recognition is to learn feature representations and a clas-sifier separately, with instance and class-balanced sampling, respectively. In this work, we introduce a new framework, by making the key observation that a feature represen-tation learned with instance sampling is far from optimal in a long-tailed ... Web3 code implementations in PyTorch. Several approaches have been proposed in recent literature to alleviate the long-tail problem, mainly in object classification tasks. In this …
WebTo correct the optimization behavior of SCL and further improve the performance of long-tailed visual recognition, we propose a novel loss for balanced contrastive learning …
Web25 de jun. de 2024 · Disentangling Label Distribution for Long-tailed Visual Recognition Abstract: The current evaluation protocol of long-tailed visual recognition trains the … short hair for round faces over 60Web22 de jul. de 2024 · Extensive experiments on multiple popular long-tailed recognition benchmarks demonstrate that the feature-balanced loss achieves superior performance … short hair for senior menshort hair for round facesWeb17 de out. de 2024 · Abstract: We tackle the long-tailed visual recognition problem from the knowledge distillation perspective by proposing a Distill the Virtual Examples (DiVE) method. Specifically, by treating the predictions of a teacher model as virtual examples, we prove that distilling from these virtual examples is equivalent to label distribution learning … short hair for senior womenWeb29 de nov. de 2024 · A Simple Long-Tailed Recognition Baseline via Vision-Language Model. Teli Ma, Shijie Geng, Mengmeng Wang, Jing Shao, Jiasen Lu, Hongsheng Li, … san joaquin sheriff\u0027s officeWebDeveloped a new classifier. Breadcrumbs: Adversarial Class-Balanced Sampling for Long-tailed Recognition (ECCV 2024) Code. Constructing Balance from Imbalance for Long … san joaquin security techWeb14 de dez. de 2024 · Data in the real world tends to exhibit a long-tailed label distribution, which poses great challenges for the training of neural networks in visual recognition. Existing methods tackle this... san joaquin sheriff\u0027s