Object Instance Mining for Weakly Supervised Object Detection 论文笔记 前言 大多数弱监督目标检测(WSOD)采用的框架是将多实例学习(MIL)和CNN结合起来,这种框架通常会将特定于某个类别的具有最高置信度的proposal挖掘出来,以训练基于CNN的分类器,但并不会考虑图像中的目标实例的数量。如果图像中有
Semantic labelling and instance segmentation are two tasks that require particularly costly annotations. Starting from weak supervision in the form of bounding box detection annotations, we propose a new approach that does not require modification of the segmentation training procedure. We show that ...
Weakly supervised learningObject detectionRegularizationWe study weakly supervised learning for object detectors, where training images have image-level class labels only. This problem is often addressed by multiple instance learning, where pseudo-labels of proposals are constructed from image-level weak ...
To investigate the infection segmentation performance of the proposed USTM-Net, we compared it with other five state-of-the-art methods, including Scribble2Label (S2L) model [44], weakly-supervised salient object detection (WSOD) method [54], partial U-Net (p-UNet) [55], weakly-supervised...
Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation Discriminative Region Suppression for Weakly-Superv...
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Our model obtains competitive performance on weakly supervised object localization and salient object detection benchmarks without fine-tuning the extent filling module for the specific tasks. The main contributions of this paper include: • The development of an inst...
Cross-frame feature-saliency mutual reinforcing for weakly supervised video salient object detection 2024, Pattern Recognition Citation Excerpt : However, pixel-level annotations are required in such models, which are time-consuming and labor-intensive. To reduce massive resources for pixel-level annotatio...
Kernelized few-shot object detection with efficient integral aggregation. In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. 2 [94] Zhilu Zhang and Mert R Sabuncu. Self-distillation as instance-specific label...
The activation of a CNN on feature maps of an image focuses on the most discriminative instance of a class despite the existence of many instances, in this case cells. Due to the design of this competition, with highly heterogeneous images in the test set, high scores required correct ...