Papers Object Localization
“Object Localization” 태그가 달린 논문 726편 · 필터 해제
Adaptively Denoising Proposal Collection forWeakly Supervised Object Localization
In this paper, we address the problem of weakly supervisedobject localization (WSL), which trains a detection network on the datasetwith only image-level annotations. The proposed approach is built on theobservation that…
DenoisingMultiple Instance LearningObjectObject Localization+1LIT: Light-field Inference of Transparency for Refractive Object Localization
Translucency is prevalent in everyday scenes. As such, perception of transparent objects is essential for robots to perform manipulation. Compared with texture-rich or texture-less Lambertian objects, transparency induce…
ObjectObject LocalizationPose EstimationTransparent objectsEmbodied Amodal Recognition: Learning to Move to Perceive Objects
Passive visual systems typically fail to recognize objects in the amodal setting where they are heavily occluded. In contrast, humans and other embodied agents have the ability to move in the environment and actively con…
ObjectObject LocalizationSemantic SegmentationInformation Entropy Based Feature Pooling for Convolutional Neural Networks
In convolutional neural networks (CNNs), we propose to estimate the importance of a feature vector at a spatial location in the feature maps by the network's uncertainty on its class prediction, which can be quantified u…
General ClassificationObject LocalizationSegmentationSemantic Segmentation+3DANet: Divergent Activation for Weakly Supervised Object Localization
Weakly supervised object localization remains a challenge when learning object localization models from image category labels. Optimizing image classification tends to activate object parts and ignore the full object ext…
ClassificationGeneral Classificationimage-classificationImage Classification+3Multi-scale discriminative Region Discovery for Weakly-Supervised Object Localization
Localizing objects with weak supervision in an image is a key problem of the research in computer vision community. Many existing Weakly-Supervised Object Localization (WSOL) approaches tackle this problem by estimating …
Object LocalizationWeakly-Supervised Object LocalizationDeep learning architectures for automated image segmentation
Image segmentation is widely used in a variety of computer vision tasks, such as object localization and recognition, boundary detection, and medical imaging. This thesis proposes deep learning architectures to improve a…
Boundary DetectionDecoderDeep LearningImage Segmentation+5NEMO: Future Object Localization Using Noisy Ego Priors
Predicting the future trajectory of agents from visual observations is an important problem for realization of safe and effective navigation of autonomous systems in dynamic environments. This paper focuses on two import…
motion predictionObjectObject LocalizationCELNet: Evidence Localization for Pathology Images using Weakly Supervised Learning
Despite deep convolutional neural networks boost the performance of image classification and segmentation in digital pathology analysis, they are usually weak in interpretability for clinical applications or require heav…
Diagnosticimage-classificationImage ClassificationObject Localization+1Dual-attention Focused Module for Weakly Supervised Object Localization
The research on recognizing the most discriminative regions provides referential information for weakly supervised object localization with only image-level annotations. However, the most discriminative regions usually c…
ObjectObject LocalizationObject RecognitionPosition+1Weakly Supervised Localization Using Background Images
Weakly Supervised Object Localization (WSOL) methodsusually rely on fully convolutional networks in order to ob-tain class activation maps(CAMs) of targeted labels. How-ever, these networks always highlight the most disc…
ObjectObject LocalizationWeakly-Supervised Object LocalizationBuilding Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors
With rapid adoption of deep learning in critical applications, the question of when and how much to trust these models often arises, which drives the need to quantify the inherent uncertainties. While identifying all sou…
Object LocalizationPredictionPrediction IntervalsTime Series+3Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A Survey
Using deep learning models to diagnose cancer from histology data presents several challenges. Cancer grading and localization of regions of interest (ROIs) in these images normally relies on both image- and pixel-level …
General ClassificationModel SelectionObject LocalizationWeakly-supervised Learning+1Attention-based Dropout Layer for Weakly Supervised Object Localization
Weakly Supervised Object Localization (WSOL) techniques learn the object location only using image-level labels, without location annotations. A common limitation for these techniques is that they cover only the most dis…
ObjectObject LocalizationWeakly-Supervised Object LocalizationSmooth Grad-CAM++: An Enhanced Inference Level Visualization Technique for Deep Convolutional Neural Network Models
Gaining insight into how deep convolutional neural network models perform image classification and how to explain their outputs have been a concern to computer vision researchers and decision makers. These deep models ar…
image-classificationImage ClassificationObject Localization"Sliced" Subwindow Search: a Sublinear-complexity Solution to the Maximum Rectangle Problem
Considering a 2D matrix of positive and negative numbers, how might one draw a rectangle within it whose contents sum higher than all other rectangles'? This fundamental problem, commonly known the maximum rectangle prob…
Object LocalizationMin-max Entropy for Weakly Supervised Pointwise Localization
Pointwise localization allows more precise localization and accurate interpretability, compared to bounding box, in applications where objects are highly unstructured such as in medical domain. In this work, we focus on …
Object LocalizationWeakly-Supervised Object LocalizationSIXray: A Large-Scale Security Inspection X-Ray Benchmark for Prohibited Item Discovery in Overlapping Images
In this paper, we present a large-scale dataset and establish a baseline for prohibited item discovery in Security Inspection X-ray images. Our dataset, named SIXray, consists of 1,059,231 X-ray images, in which 6 classe…
Object LocalizationLearning 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+7Enabling Computer Vision Driven Assistive Devices for the Visually Impaired via Micro-architecture Design Exploration
Recent improvements in object detection have shown potential to aid in tasks where previous solutions were not able to achieve. A particular area is assistive devices for individuals with visual impairment. While state-o…
Objectobject-detectionObject DetectionObject Localization