Papers Object Localization
“Object Localization” 태그가 달린 논문 726편 · 필터 해제
Spatial-Aware Token for Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) is a challenging task aiming to localize objects with only image-level supervision. Recent works apply visual transformer to WSOL and achieve significant success by exploiting…
ObjectObject LocalizationWeakly-Supervised Object LocalizationDiffusionSeg: Adapting Diffusion Towards Unsupervised Object Discovery
Learning from a large corpus of data, pre-trained models have achieved impressive progress nowadays. As popular generative pre-training, diffusion models capture both low-level visual knowledge and high-level semantic re…
ObjectObject DiscoveryObject LocalizationCoLo-CAM: Class Activation Mapping for Object Co-Localization in Weakly-Labeled Unconstrained Videos
Leveraging spatiotemporal information in videos is critical for weakly supervised video object localization (WSVOL) tasks. However, state-of-the-art methods only rely on visual and motion cues, while discarding discrimin…
ObjectObject LocalizationQuery-guided Attention in Vision Transformers for Localizing Objects Using a Single Sketch
In this work, we investigate the problem of sketch-based object localization on natural images, where given a crude hand-drawn sketch of an object, the goal is to localize all the instances of the same object on the targ…
Objectobject-detectionObject DetectionObject LocalizationFingerSLAM: Closed-loop Unknown Object Localization and Reconstruction from Visuo-tactile Feedback
In this paper, we address the problem of using visuo-tactile feedback for 6-DoF localization and 3D reconstruction of unknown in-hand objects. We propose FingerSLAM, a closed-loop factor graph-based pose estimator that c…
3D ReconstructionObject LocalizationPose EstimationMultiparticle Kalman filter for object localization in symmetric environments
This study considers the object localization problem and proposes a novel multiparticle Kalman filter to solve it in complex and symmetric environments. Two well-known classes of filtering algorithms to solve the localiz…
Object LocalizationJoint ANN-SNN Co-training for Object Localization and Image Segmentation
The field of machine learning has been greatly transformed with the advancement of deep artificial neural networks (ANNs) and the increased availability of annotated data. Spiking neural networks (SNNs) have recently eme…
Image Segmentationobject-detectionObject DetectionObject Localization+13D-Aware Object Localization using Gaussian Implicit Occupancy Function
To automatically localize a target object in an image is crucial for many computer vision applications. To represent the 2D object, ellipse labels have recently been identified as a promising alternative to axis-aligned …
ObjectObject LocalizationPose EstimationSpacecraft Pose EstimationConfidence-driven Bounding Box Localization for Small Object Detection
Despite advancements in generic object detection, there remains a performance gap in detecting small objects compared to normal-scale objects. We for the first time observe that existing bounding box regression methods t…
Objectobject-detectionObject DetectionObject Localization+2Deep Learning for Identifying Iran's Cultural Heritage Buildings in Need of Conservation Using Image Classification and Grad-CAM
The cultural heritage buildings (CHB), which are part of mankind's history and identity, are in constant danger of damage or in extreme situations total destruction. That being said, it's of utmost importance to preserve…
Data Augmentationimage-classificationImage ClassificationObject Localization+1NU-AIR -- A Neuromorphic Urban Aerial Dataset for Detection and Localization of Pedestrians and Vehicles
This paper presents an open-source aerial neuromorphic dataset that captures pedestrians and vehicles moving in an urban environment. The dataset, titled NU-AIR, features 70.75 minutes of event footage acquired with a 64…
Object LocalizationPedestrian DetectionAn Application of Deep Learning for Sweet Cherry Phenotyping using YOLO Object Detection
Tree fruit breeding is a long-term activity involving repeated measurements of various fruit quality traits on a large number of samples. These traits are traditionally measured by manually counting the fruits, weighing …
object-detectionObject DetectionObject LocalizationFew-Shot Object Detection via Variational Feature Aggregation
As few-shot object detectors are often trained with abundant base samples and fine-tuned on few-shot novel examples,the learned models are usually biased to base classes and sensitive to the variance of novel examples. T…
Few-Shot Object DetectionMeta-LearningObjectobject-detection+2RREx-BoT: Remote Referring Expressions with a Bag of Tricks
Household robots operate in the same space for years. Such robots incrementally build dynamic maps that can be used for tasks requiring remote object localization. However, benchmarks in robot learning often test general…
ObjectObject LocalizationObject Preserving Siamese Network for Single Object Tracking on Point Clouds
Obviously, the object is the key factor of the 3D single object tracking (SOT) task. However, previous Siamese-based trackers overlook the negative effects brought by randomly dropped object points during backbone sampli…
3D Single Object TrackingObjectObject LocalizationObject TrackingCLIP the Gap: A Single Domain Generalization Approach for Object Detection
Single Domain Generalization (SDG) tackles the problem of training a model on a single source domain so that it generalizes to any unseen target domain. While this has been well studied for image classification, the lite…
Domain Generalizationimage-classificationImage ClassificationLanguage Modeling+5Knowledge-guided Causal Intervention for Weakly-supervised Object Localization
Previous weakly-supervised object localization (WSOL) methods aim to expand activation map discriminative areas to cover the whole objects, yet neglect two inherent challenges when relying solely on image-level labels. F…
Knowledge DistillationObjectObject LocalizationWeakly-Supervised Object LocalizationLearning Multi-Modal Class-Specific Tokens for Weakly Supervised Dense Object Localization
Weakly supervised dense object localization (WSDOL) relies generally on Class Activation Mapping (CAM), which exploits the correlation between the class weights of the image classifier and the pixel-level features. D…
Object LocalizationRepresentation LearningSemantic SegmentationWeakly supervised Semantic Segmentation+1Adversarial Normalization: I Can Visualize Everything (ICE)
Vision transformers use [CLS] tokens to predict image classes. Their explainability visualization has been studied using relevant information from [CLS] tokens or focusing on attention scores during self-attention. S…
Object DiscoveryObject LocalizationWeakly-Supervised Object LocalizationDiscriminating Known From Unknown Objects via Structure-Enhanced Recurrent Variational AutoEncoder
Discriminating known from unknown objects is an important essential ability for human beings. To simulate this ability, a task of unsupervised out-of-distribution object detection (OOD-OD) is proposed to detect the o…
Objectobject-detectionObject DetectionObject Localization