Papers Object Localization
“Object Localization” 태그가 달린 논문 726편 · 필터 해제
OCDet: Object Center Detection via Bounding Box-Aware Heatmap Prediction on Edge Devices with NPUs
Real-time object localization on edge devices is fundamental for numerous applications, ranging from surveillance to industrial automation. Traditional frameworks, such as object detection, segmentation, and keypoint det…
Keypoint DetectionObjectobject-detectionObject Detection+1Time is on my sight: scene graph filtering for dynamic environment perception in an LLM-driven robot
Robots are increasingly being used in dynamic environments like workplaces, hospitals, and homes. As a result, interactions with robots must be simple and intuitive, with robots perception adapting efficiently to human-i…
Object LocalizationTask PlanningYCB-LUMA: YCB Object Dataset with Luminance Keying for Object Localization
Localizing target objects in images is an important task in computer vision. Often it is the first step towards solving a variety of applications in autonomous driving, maintenance, quality insurance, robotics, and augme…
2D Object DetectionAutonomous DrivingObjectobject-detection+2FAST-Splat: Fast, Ambiguity-Free Semantics Transfer in Gaussian Splatting
We present FAST-Splat for fast, ambiguity-free semantic Gaussian Splatting, which seeks to address the main limitations of existing semantic Gaussian Splatting methods, namely: slow training and rendering speeds; high me…
Dimensionality ReductionGPUNatural Language QueriesObject Localization+3Text-guided Zero-Shot Object Localization
Object localization is a hot issue in computer vision area, which aims to identify and determine the precise location of specific objects from image or video. Most existing object localization methods heavily rely on ext…
ObjectObject LocalizationVisual-Linguistic Agent: Towards Collaborative Contextual Object Reasoning
Multimodal Large Language Models (MLLMs) excel at descriptive tasks within images but often struggle with precise object localization, a critical element for reliable visual interpretation. In contrast, traditional objec…
DescriptiveObjectobject-detectionObject Detection+3DynaMem: Online Dynamic Spatio-Semantic Memory for Open World Mobile Manipulation
Significant progress has been made in open-vocabulary mobile manipulation, where the goal is for a robot to perform tasks in any environment given a natural language description. However, most current systems assume a st…
Object LocalizationUpsampling DINOv2 features for unsupervised vision tasks and weakly supervised materials segmentation
The features of self-supervised vision transformers (ViTs) contain strong semantic and positional information relevant to downstream tasks like object localization and segmentation. Recent works combine these features wi…
Clusteringgraph partitioningObject LocalizationProperty Prediction+2LUDVIG: Learning-free Uplifting of 2D Visual features to Gaussian Splatting scenes
We address the problem of extending the capabilities of vision foundation models such as DINO, SAM, and CLIP, to 3D tasks. Specifically, we introduce a novel method to uplift 2D image features into Gaussian Splatting rep…
3D geometryobject-detectionObject DetectionObject Localization+2Co-Segmentation without any Pixel-level Supervision with Application to Large-Scale Sketch Classification
This work proposes a novel method for object co-segmentation, i.e. pixel-level localization of a common object in a set of images, that uses no pixel-level supervision for training. Two pre-trained Vision Transformer (Vi…
Object LocalizationSketch RecognitionOptimizing Multi-Task Learning for Accurate Spacecraft Pose Estimation
Accurate satellite pose estimation is crucial for autonomous guidance, navigation, and control (GNC) systems in in-orbit servicing (IOS) missions. This paper explores the impact of different tasks within a multi-task lea…
Multi-Task LearningObject LocalizationPose EstimationSpacecraft Pose EstimationTraining-Free Open-Ended Object Detection and Segmentation via Attention as Prompts
Existing perception models achieve great success by learning from large amounts of labeled data, but they still struggle with open-world scenarios. To alleviate this issue, researchers introduce open-set perception tasks…
Instance SegmentationObjectobject-detectionObject Detection+3PuzzleBoard: A New Camera Calibration Pattern with Position Encoding
Accurate camera calibration is a well-known and widely used task in computer vision that has been researched for decades. However, the standard approach based on checkerboard calibration patterns has some drawbacks that …
Camera CalibrationCamera Pose EstimationObject LocalizationPose Estimation+1A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation
Low-shot object counters estimate the number of objects in an image using few or no annotated exemplars. Objects are localized by matching them to prototypes, which are constructed by unsupervised image-wide object appea…
Exemplar-Free CountingFew-shot Object Counting and DetectionObjectObject Counting+3DIAL: Dense Image-text ALignment for Weakly Supervised Semantic Segmentation
Weakly supervised semantic segmentation (WSSS) approaches typically rely on class activation maps (CAMs) for initial seed generation, which often fail to capture global context due to limited supervision from image-level…
Contrastive LearningObject LocalizationSemantic SegmentationWeakly supervised Semantic Segmentation+1QUB-PHEO: A Visual-Based Dyadic Multi-View Dataset for Intention Inference in Collaborative Assembly
QUB-PHEO introduces a visual-based, dyadic dataset with the potential of advancing human-robot interaction (HRI) research in assembly operations and intention inference. This dataset captures rich multimodal interactions…
Object LocalizationPMR-Net: Parallel Multi-Resolution Encoder-Decoder Network Framework for Medical Image Segmentation
In recent years, encoder-decoder networks have focused on expanding receptive fields and incorporating multi-scale context to capture global features for objects of varying sizes. However, as networks deepen, they often …
DecoderImage SegmentationMedical Image SegmentationObject Localization+1Do Pre-trained Vision-Language Models Encode Object States?
For a vision-language model (VLM) to understand the physical world, such as cause and effect, a first step is to capture the temporal dynamics of the visual world, for example how the physical states of objects evolve ov…
Language ModelingLanguage ModellingObjectObject Localization+1Top-GAP: Integrating Size Priors in CNNs for more Interpretability, Robustness, and Bias Mitigation
This paper introduces Top-GAP, a novel regularization technique that enhances the explainability and robustness of convolutional neural networks. By constraining the spatial size of the learned feature representation, ou…
Object LocalizationPrediction Accuracy & Reliability: Classification and Object Localization under Distribution Shift
Natural distribution shift causes a deterioration in the perception performance of convolutional neural networks (CNNs). This comprehensive analysis for real-world traffic data addresses: 1) investigating the effect of n…
Autonomous DrivingBenchmarkingObject LocalizationUncertainty Quantification