Long-tailed visual recognition

Author: djlf

August undefined, 2024

WebAlmost all long-tailed methods perform better than the Softmax baseline in terms of accuracy, which demonstrates the effectiveness of long-tailed learning. Training with … Web13 de mai. de 2024 · Fig. 3 summarizes their differences. The newly proposed Open Long-Tailed Recognition (OLTR) serves as a more comprehensive and more realistic …

Balanced Meta-Softmax for Long-Tailed Visual Recognition

Web22 de mar. de 2024 · Attentive Feature Augmentation for Long-Tailed Visual Recognition. Abstract: Deep neural networks have achieved great success on many visual … 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 … spice herald

Balanced Meta-Softmax for Long-Tailed Visual Recognition

Web14 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... Web14 de abr. de 2024 · Most recent studies focus on general long-tailed recognition, however, limited effort has been made for long-tailed time series classification due to the lack of proper benchmarks. Inspired by this, we construct three benchmarks to fill the gap and design hierarchical prototypes based on temporal properties to ensure semantic … Web22 de mar. de 2024 · Attentive Feature Augmentation for Long-Tailed Visual Recognition Abstract: Deep neural networks have achieved great success on many visual recognition tasks. However, training data with a long-tailed distribution dramatically degenerates the performance of recognition models. spice heritage attleborough

Feature-Balanced Loss for Long-Tailed Visual Recognition

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 … WebTowards Visual Recognition in the Wild: Long-Tailed Sources and Open Compound Targets spice herbs trade utensilsWeb29 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, … spice hill wallingford ct

"Web27 de mai. de 2024 · In this survey, we focus on the problems caused by long-tailed data distribution, sort out the representative long-tailed visual recognition datasets and summarize some mainstream long-tailed studies. " - Long-tailed visual recognition

Long-tailed visual recognition

Web12 de abr. de 2024 · An effective and simple approach to long-tailed visual recognition is to learn feature representations and a classifier separately, with instance and class-balanced sampling, respectively. In this work, we introduce a new framework, by making the key observation that a feature representation learned with instance sampling is far from … Web24 de jun. de 2024 · To correct the optimization behavior of SCL and further improve the performance of long-tailed visual recognition, we propose a novel loss for balanced …

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Web14 de out. de 2024 · To the best of our knowledge, this is the first study that aims to identify and evaluate methods systematically for long-tailed visual recognition. We provide a … 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 ...

Weblong-tail visual recognition tasks in a uniﬁed framework. Below we start with a brief introduction to the long-tail classiﬁcation and an empirical study of two-stage methods in Sec.3.1. We then describe our proposed distribution align-ment strategy in Sec.3.2. Finally, we present a comparison with previous methods from the distribution ... Web27 de mai. de 2024 · In this survey, we focus on the problems caused by long-tailed data distribution, sort out the representative long-tailed visual recognition datasets and summarize some mainstream long-tailed ...

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 ... WebLong-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation Yan Jin · Mengke LI · Yang Lu · Yiu-ming Cheung · Hanzi Wang Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation Chaohui Yu · Qiang Zhou · Jingliang Li · Jianlong Yuan · Zhibin Wang · Fan Wang

Web14 de out. de 2024 · To the best of our knowledge, this is the first study that aims to identify and evaluate methods systematically for long-tailed visual recognition. We …

Webfour standard long-tailed image recognition benchmarks. Besides, we validate the effectiveness of IEM on a long-tailed video recognition benchmark, i.e., YouTube-8M. 1. Introduction Recently, visual recognition models [20,14] have achieved signiﬁcant success with the renaissance of deep convolutional neural networks (ConvNets). These … spice herbalsWeb11 de abr. de 2024 · Improving Image Recognition by Retrieving from Web-Scale Image-Text Data. Retrieval augmented models are becoming increasingly popular for computer vision tasks after their recent success in NLP problems. The goal is to enhance the recognition capabilities of the model by retrieving similar examples for the visual input … spice holdco limitedWeb21 de jul. de 2024 · Deep classifiers have achieved great success in visual recognition. However, real-world data is long-tailed by nature, leading to the mismatch between training and testing distributions. In this paper, we show that Softmax function, though used in most classification tasks, gives a biased gradient estimation under the long-tailed setup. spice high level disinfectionhttp://ffmpbgrnn.github.io/publications/pdf/iem.pdf spice hill warwick bermudaWeb14 de nov. de 2024 · Long-Tailed ImageNet. The long-tailed ImageNet (ImageNet-LT) is derived from the original ImageNet-2012 by sampling a subset following the Pareto … spice home adreseWeb25 de jun. de 2024 · Abstract: The current evaluation protocol of long-tailed visual recognition trains the classification model on the long-tailed source label distribution and evaluates its performance on the uniform target label distribution. Such protocol has questionable practicality since the target may also be long-tailed. Therefore, we … spice holdingsWebDeveloped a new classifier. Breadcrumbs: Adversarial Class-Balanced Sampling for Long-tailed Recognition (ECCV 2024) Code. Constructing Balance from Imbalance for Long … spice hiccups