Papers Image-level Supervised Instance Segmentation
“Image-level Supervised Instance Segmentation” 태그가 달린 논문 14편 · 필터 해제
WeakSAM: Segment Anything Meets Weakly-supervised Instance-level Recognition
Weakly supervised visual recognition using inexact supervision is a critical yet challenging learning problem. It significantly reduces human labeling costs and traditionally relies on multi-instance learning and pseudo-…
Image-level Supervised Instance Segmentationobject-detectionObject DetectionSegmentation+2Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-Refinement
Weakly-supervised instance segmentation (WSIS) has been considered as a more challenging task than weakly-supervised semantic segmentation (WSSS). Compared to WSSS, WSIS requires instance-wise localization, which is diff…
Image-level Supervised Instance SegmentationInstance SegmentationPoint-Supervised Instance SegmentationSegmentation+5Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation
Weakly supervised semantic instance segmentation with only image-level supervision, instead of relying on expensive pixel wise masks or bounding box annotations, is an important problem to alleviate the data-hungry natur…
Image-level Supervised Instance SegmentationInstance SegmentationMultiple Instance LearningSegmentation+3Weakly Supervised Instance Segmentation by Learning Annotation Consistent Instances
Recent approaches for weakly supervised instance segmentations depend on two components: (i) a pseudo label generation model that provides instances which are consistent with a given annotation; and (ii) an instance segm…
Image-level Supervised Instance SegmentationInstance SegmentationPseudo LabelSegmentation+2Weakly Supervised Instance Segmentation by Deep Community Learning
We present a weakly supervised instance segmentation algorithm based on deep community learning with multiple tasks. This task is formulated as a combination of weakly supervised object detection and semantic segmentatio…
Image-level Supervised Instance SegmentationInstance Segmentationobject-detectionObject Detection+4Towards Partial Supervision for Generic Object Counting in Natural Scenes
Generic object counting in natural scenes is a challenging computer vision problem. Existing approaches either rely on instance-level supervision or absolute count information to train a generic object counter. We introd…
image-classificationImage ClassificationImage-level Supervised Instance SegmentationInstance Segmentation+3Label-PEnet: Sequential Label Propagation and Enhancement Networks for Weakly Supervised Instance Segmentation
Weakly-supervised instance segmentation aims to detect and segment object instances precisely, given imagelevel labels only. Unlike previous methods which are composed of multiple offline stages, we propose Sequential La…
General ClassificationImage-level Supervised Instance SegmentationInstance SegmentationMulti-Label Classification+6Where are the Masks: Instance Segmentation with Image-level Supervision
A major obstacle in instance segmentation is that existing methods often need many per-pixel labels in order to be effective. These labels require large human effort and for certain applications, such labels are not read…
Image-level Supervised Instance SegmentationInstance SegmentationSemantic SegmentationCyclic Guidance for Weakly Supervised Joint Detection and Segmentation
Weakly supervised learning has attracted growing research attention due to the significant saving in annotation cost for tasks that require intra-image annotations, such as object detection and semantic segmentation. To …
Image-level Supervised Instance SegmentationMulti-Task LearningObjectobject-detection+5Learning Instance Activation Maps for Weakly Supervised Instance Segmentation
Discriminative region responses residing inside an object instance can be extracted from networks trained with image-level label supervision. However, learning the full extent of pixel-level instance response in a weakly…
Image-level Supervised Instance SegmentationInstance SegmentationObjectobject-detection+7Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations
This paper presents a novel approach for learning instance segmentation with image-level class labels as supervision. Our approach generates pseudo instance segmentation labels of training images, which are used to train…
image-classificationImage ClassificationImage-level Supervised Instance SegmentationInstance Segmentation+3Object Counting and Instance Segmentation with Image-level Supervision
Common object counting in a natural scene is a challenging problem in computer vision with numerous real-world applications. Existing image-level supervised common object counting approaches only predict the global objec…
Image-level Supervised Instance SegmentationInstance SegmentationObjectObject Counting+1Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation
Effectively bridging between image level keyword annotations and corresponding image pixels is one of the main challenges in weakly supervised semantic segmentation. In this paper, we use an instance-level salient object…
Clusteringgraph partitioningImage-level Supervised Instance SegmentationInstance Segmentation+6Weakly Supervised Instance Segmentation using Class Peak Response
Weakly supervised instance segmentation with image-level labels, instead of expensive pixel-level masks, remains unexplored. In this paper, we tackle this challenging problem by exploiting class peak responses to enable …
General ClassificationImage-level Supervised Instance SegmentationInstance SegmentationSegmentation+2