Papers Object Localization
“Object Localization” 태그가 달린 논문 726편 · 필터 해제
Unsupervised Learning Layers for Video Analysis
This paper presents two unsupervised learning layers (UL layers) for label-free video analysis: one for fully connected layers, and the other for convolutional ones. The proposed UL layers can play two roles: they can be…
Object LocalizationHow hard can it be? Estimating the difficulty of visual search in an image
We address the problem of estimating image difficulty defined as the human response time for solving a visual search task. We collect human annotations of image difficulty for the PASCAL VOC 2012 data set through a crowd…
Object LocalizationWeakly-Supervised Object LocalizationTraining object class detectors with click supervision
Training object class detectors typically requires a large set of images with objects annotated by bounding boxes. However, manually drawing bounding boxes is very time consuming. In this paper we greatly reduce annotati…
Multiple Instance LearningObjectObject LocalizationWeakly-Supervised Object LocalizationDeep Self-Taught Learning for Weakly Supervised Object Localization
Most existing weakly supervised localization (WSL) approaches learn detectors by finding positive bounding boxes based on features learned with image-level supervision. However, those features do not contain spatial loca…
ObjectObject LocalizationWeakly Supervised Object DetectionWeakly-Supervised Object LocalizationHide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization
We propose `Hide-and-Seek', a weakly-supervised framework that aims to improve object localization in images and action localization in videos. Most existing weakly-supervised methods localize only the most discriminativ…
Action LocalizationObjectObject LocalizationWeakly Supervised Action Localization+1DeNet: Scalable Real-time Object Detection with Directed Sparse Sampling
We define the object detection from imagery problem as estimating a very large but extremely sparse bounding box dependent probability distribution. Subsequently we identify a sparse distribution estimation scheme, Direc…
object-detectionObject DetectionObject LocalizationReal-Time Object DetectionBootstrapping Labelled Dataset Construction for Cow Tracking and Behavior Analysis
This paper introduces a new approach to the long-term tracking of an object in a challenging environment. The object is a cow and the environment is an enclosure in a cowshed. Some of the key challenges in this domain ar…
Instance SegmentationObjectObject LocalizationObject Tracking+1Gaussian Processes with Context-Supported Priors for Active Object Localization
We devise an algorithm using a Bayesian optimization framework in conjunction with contextual visual data for the efficient localization of objects in still images. Recent research has demonstrated substantial progress i…
Active Object LocalizationBayesian OptimizationGaussian ProcessesObject+2Count-ception: Counting by Fully Convolutional Redundant Counting
Counting objects in digital images is a process that should be replaced by machines. This tedious task is time consuming and prone to errors due to fatigue of human annotators. The goal is to have a system that takes as …
Object LocalizationregressionWeakly Supervised Object Localization Using Things and Stuff Transfer
We propose to help weakly supervised object localization for classes where location annotations are not available, by transferring things and stuff knowledge from a source set with available annotations. The source and t…
Multiple Instance LearningObjectObject LocalizationSegmentation+1Mask R-CNN
We present a conceptually simple, flexible, and general framework for object instance segmentation. Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask fo…
3D Instance SegmentationHuman Part SegmentationInstance SegmentationKeypoint Detection+14Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World
Bridging the 'reality gap' that separates simulated robotics from experiments on hardware could accelerate robotic research through improved data availability. This paper explores domain randomization, a simple technique…
Object LocalizationVision-based Real-Time Aerial Object Localization and Tracking for UAV Sensing System
The paper focuses on the problem of vision-based obstacle detection and tracking for unmanned aerial vehicle navigation. A real-time object localization and tracking strategy from monocular image sequences is developed b…
Objectobject-detectionObject DetectionObject LocalizationTree-Structured Reinforcement Learning for Sequential Object Localization
Existing object proposal algorithms usually search for possible object regions over multiple locations and scales separately, which ignore the interdependency among different objects and deviate from the human perception…
DiversityObjectObject Localizationreinforcement-learning+2Collaborative Deep Reinforcement Learning for Joint Object Search
We examine the problem of joint top-down active search of multiple objects under interaction, e.g., person riding a bicycle, cups held by the table, etc.. Such objects under interaction often can provide contextual cues …
Active Object LocalizationDeep Reinforcement LearningObjectobject-detection+6Tracking using Numerous Anchor points
In this paper, an online adaptive model-free tracker is proposed to track single objects in video sequences to deal with real-world tracking challenges like low-resolution, object deformation, occlusion and motion blur. …
ObjectObject LocalizationVisual TrackingCo-localization with Category-Consistent Features and Geodesic Distance Propagation
Co-localization is the problem of localizing objects of the same class using only the set of images that contain them. This is a challenging task because the object detector must be built without negative examples that c…
image-classificationImage ClassificationObjectObject Discovery+1Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model
In this paper, a self-learning approach is proposed towards solving scene-specific pedestrian detection problem without any human' annotation involved. The self-learning approach is deployed as progressive steps of objec…
ObjectObject DiscoveryObject LocalizationPedestrian Detection+3Fast On-Line Kernel Density Estimation for Active Object Localization
A major goal of computer vision is to enable computers to interpret visual situations---abstract concepts (e.g., "a person walking a dog," "a crowd waiting for a bus," "a picnic") whose image instantiations are linked mo…
Active Object LocalizationDensity EstimationObject LocalizationContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization
We aim to localize objects in images using image-level supervision only. Previous approaches to this problem mainly focus on discriminative object regions and often fail to locate precise object boundaries. We address th…
ObjectObject LocalizationObject RecognitionWeakly Supervised Object Detection+1