Papers Object Localization
“Object Localization” 태그가 달린 논문 726편 · 필터 해제
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality. To interface a highly sparse LiDAR point clou…
3D Object DetectionBirds Eye View Object DetectionDescriptiveFeature Engineering+3Improving Object Localization with Fitness NMS and Bounded IoU Loss
We demonstrate that many detection methods are designed to identify only a sufficently accurate bounding box, rather than the best available one. To address this issue we propose a simple and fast modification to the exi…
ClusteringObject LocalizationGrad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
Over the last decade, Convolutional Neural Network (CNN) models have been highly successful in solving complex vision problems. However, these deep models are perceived as "black box" methods considering the lack of unde…
3D Action RecognitionAction RecognitionCaption GenerationError Understanding+3Class Correlation affects Single Object Localization using Pre-trained ConvNets
The problem of object localization has become one of the mainstream problems of vision. Most of the algorithms proposed involve the design for the model to be specifically for localizing objects. In this paper, we explor…
ObjectObject LocalizationProgressive Representation Adaptation for Weakly Supervised Object Localization
We address the problem of weakly supervised object localization where only image-level annotations are available for training object detectors. Numerous methods have been proposed to tackle this problem through mining ob…
ClassificationGeneral ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+4Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video
Object detection is considered one of the most challenging problems in this field of computer vision, as it involves the combination of object classification and object localization within a scene. Recently, deep neural …
GPUObjectobject-detectionObject Detection+2Locating 3D Object Proposals: A Depth-Based Online Approach
2D object proposals, quickly detected regions in an image that likely contain an object of interest, are an effective approach for improving the computational efficiency and accuracy of object detection in color images. …
Computational EfficiencyCPUObjectobject-detection+2Soft Proposal Networks for Weakly Supervised Object Localization
Weakly supervised object localization remains challenging, where only image labels instead of bounding boxes are available during training. Object proposal is an effective component in localization, but often computation…
ObjectObject LocalizationWeakly Supervised Object DetectionWeakly-Supervised Object LocalizationSTNet: Selective Tuning of Convolutional Networks for Object Localization
Visual attention modeling has recently gained momentum in developing visual hierarchies provided by Convolutional Neural Networks. Despite recent successes of feedforward processing on the abstraction of concepts form ra…
ObjectObject LocalizationTwo-Phase Learning for Weakly Supervised Object Localization
Weakly supervised semantic segmentation and localiza- tion have a problem of focusing only on the most important parts of an image since they use only image-level annota- tions. In this paper, we solve this problem funda…
ObjectObject LocalizationSegmentationSemantic Segmentation+5Motion-Appearance Interactive Encoding for Object Segmentation in Unconstrained Videos
We present a novel method of integrating motion and appearance cues for foreground object segmentation in unconstrained videos. Unlike conventional methods encoding motion and appearance patterns individually, our method…
Graph MatchingObjectObject LocalizationSemantic Segmentation+13DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-scale 3D Point Clouds
Semantic parsing of large-scale 3D point clouds is an important research topic in computer vision and remote sensing fields. Most existing approaches utilize hand-crafted features for each modality independently and comb…
ClassificationDeep Reinforcement LearningGeneral Classificationimage-classification+5Object-Extent Pooling for Weakly Supervised Single-Shot Localization
In the face of scarcity in detailed training annotations, the ability to perform object localization tasks in real-time with weak-supervision is very valuable. However, the computational cost of generating and evaluating…
ObjectObject LocalizationRegion ProposalWeakly-Supervised Object LocalizationAutomatic Construction of Real-World Datasets for 3D Object Localization using Two Cameras
Unlike classification, position labels cannot be assigned manually by humans. For this reason, generating supervision for precise object localization is a hard task. This paper details a method to create large datasets f…
General ClassificationObjectObject LocalizationPositionRON: Reverse Connection with Objectness Prior Networks for Object Detection
We present RON, an efficient and effective framework for generic object detection. Our motivation is to smartly associate the best of the region-based (e.g., Faster R-CNN) and region-free (e.g., SSD) methodologies. Under…
GPUObjectobject-detectionObject Detection+1WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation
This paper introduces WILDCAT, a deep learning method which jointly aims at aligning image regions for gaining spatial invariance and learning strongly localized features. Our model is trained using only global image lab…
General Classificationimage-classificationImage ClassificationObject Localization+4Iterative Spectral Clustering for Unsupervised Object Localization
This paper addresses the problem of unsupervised object localization in an image. Unlike previous supervised and weakly supervised algorithms that require bounding box or image level annotations for training classifiers …
ClusteringObjectObject DiscoveryObject Localization+1Weakly supervised training of deep convolutional neural networks for overhead pedestrian localization in depth fields
Overhead depth map measurements capture sufficient amount of information to enable human experts to track pedestrians accurately. However, fully automating this process using image analysis algorithms can be challenging.…
Data AugmentationObject LocalizationEnsemble of Part Detectors for Simultaneous Classification and Localization
Part-based representation has been proven to be effective for a variety of visual applications. However, automatic discovery of discriminative parts without object/part-level annotations is challenging. This paper propos…
ClassificationClusteringDiversityGeneral Classification+4Dilated Residual Networks
Convolutional networks for image classification progressively reduce resolution until the image is represented by tiny feature maps in which the spatial structure of the scene is no longer discernible. Such loss of spati…
ClassificationGeneral Classificationimage-classificationImage Classification+3