WebExploring Classification Equilibrium in Long-Tailed Object Detection (LOCE, ICCV 2024) Paper Website. Introduction. The conventional detectors tend to make imbalanced … WebDespite the recent success of long-tailed object detec-tion, almost all long-tailed object detectors are developed based on the two-stage paradigm. In practice, one-stage detectors are more prevalent in the industry because they have a simple and fast pipeline that is easy to deploy. How-ever, in the long-tailed scenario, this line of work has not

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Web1 code implementation in PyTorch. Object recognition techniques using convolutional neural networks (CNN) have achieved great success. However, state-of-the-art object detection methods still perform poorly on large vocabulary and long-tailed datasets, e.g. LVIS. In this work, we analyze this problem from a novel perspective: each positive sample of one … safari pants for women

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Web15 de dez. de 2024 · In this paper, we reveal the main issue in long-tailed object detection is the imbalanced gradients between positives and negatives, and find that EQL does not solve it well. To address the ... WebSelf-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition. Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning. ... Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset. Web1 de jan. de 2024 · However, object quantities of different categories are subjected to long-tailed Zipfian distribution in realistic scenario and such characteristic leads to a … isha life online store