SOTAVerified

Object Localization

Object Localization is the task of locating an instance of a particular object category in an image, typically by specifying a tightly cropped bounding box centered on the instance. An object proposal specifies a candidate bounding box, and an object proposal is said to be a correct localization if it sufficiently overlaps a human-labeled “ground-truth” bounding box for the given object. In the literature, the “Object Localization” task is to locate one instance of an object category, whereas “object detection” focuses on locating all instances of a category in a given image.

Source: Fast On-Line Kernel Density Estimation for Active Object Localization

Papers

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Showing 501–550 of 617 papers

TitleStatusHype
Calibrating Uncertainties in Object Localization Task—0
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object LocalizationCode0
Identify, locate and separate: Audio-visual object extraction in large video collections using weak supervision—0
Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and BeyondCode0
Flash Photography for Data-Driven Hidden Scene Recovery—0
ML-LocNet: Improving Object Localization with Multi-view Learning Network—0
Holistic 3D Scene Parsing and Reconstruction from a Single RGB ImageCode0
Object Localization and Size Estimation from RGB-D Images—0
Deep Learning Methods and Applications for Region of Interest Detection in Dermoscopic Images—0
Self-produced Guidance for Weakly-supervised Object LocalizationCode0
In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization—0
A Generic Approach to Lung Field Segmentation from Chest Radiographs using Deep Space and Shape Learning—0
Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving—0
Plenoptic Monte Carlo Object Localization for Robot Grasping under Layered Translucency—0
Learning Object Localization and 6D Pose Estimation from Simulation and Weakly Labeled Real Images—0
Visually Guided Spatial Relation Extraction from Text—0
Generative Adversarial Networks for Unsupervised Object Co-localization—0
Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation—0
Object Localization with a Weakly Supervised CapsNet—0
Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation—0
Learning to Grasp Without Seeing—0
Localization: A Missing Link in the Pipeline of Object Matching and Registration—0
Adapting Mask-RCNN for Automatic Nucleus Segmentation—0
Adversarial Complementary Learning for Weakly Supervised Object LocalizationCode0
Fusing Saliency Maps with Region Proposals for Unsupervised Object Localization—0
FPAN: Fine-grained and Progressive Attention Localization Network for Data Retrieval—0
Exploring to learn visual saliency: The RL-IAC approach—0
Weakly Supervised Object Localization on grocery shelves using simple FCN and Synthetic Dataset—0
The Earth ain't Flat: Monocular Reconstruction of Vehicles on Steep and Graded Roads from a Moving CameraCode0
A Non-Technical Survey on Deep Convolutional Neural Network Architectures—0
Tell Me Where to Look: Guided Attention Inference NetworkCode0
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning—0
Attention-Aware Generative Adversarial Networks (ATA-GANs)—0
Improved Techniques For Weakly-Supervised Object Localization—0
Tiny SSD: A Tiny Single-shot Detection Deep Convolutional Neural Network for Real-time Embedded Object DetectionCode0
End-to-end detection-segmentation network with ROI convolutionCode0
Particle filter re-detection for visual tracking via correlation filters—0
Distance to Center of Mass Encoding for Instance SegmentationCode0
Improving Object Localization with Fitness NMS and Bounded IoU LossCode0
Class Correlation affects Single Object Localization using Pre-trained ConvNets—0
Progressive Representation Adaptation for Weakly Supervised Object LocalizationCode0
Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in VideoCode0
Locating 3D Object Proposals: A Depth-Based Online Approach—0
Soft Proposal Networks for Weakly Supervised Object LocalizationCode0
STNet: Selective Tuning of Convolutional Networks for Object Localization—0
Two-Phase Learning for Weakly Supervised Object Localization—0
Motion-Appearance Interactive Encoding for Object Segmentation in Unconstrained Videos—0
3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-scale 3D Point Clouds—0
Object-Extent Pooling for Weakly Supervised Single-Shot Localization—0
Automatic Construction of Real-World Datasets for 3D Object Localization using Two Cameras—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OSMaNRGSPL32.99—Unverified
2SUSARGSPL27.31—Unverified
3ShanksRGSPL22.85—Unverified
4CVPR22RGSPL22.06—Unverified
5damm1RGSPL15.96—Unverified
61637RGSPL14.03—Unverified
7init. PREVALENTRGSPL13.51—Unverified
8AirbertRGSPL13.28—Unverified
9init. OSCARRGSPL10—Unverified
10SIARGSPL9.2—Unverified
#ModelMetricClaimedVerifiedStatus
1VoxelNetAP89.35—Unverified
2VoxelNetAP89.35—Unverified
3Frustum PointNetsAP88.7—Unverified
4Frustum PointNetsAP81.2—Unverified
5VoxelNetAP77.47—Unverified
#ModelMetricClaimedVerifiedStatus
1Frustrum-PointPillarsAP48.3—Unverified
2Frustum PointNetsAP47.2—Unverified
3Frustum PointNetsAP40.23—Unverified
4VoxelNetAP38.11—Unverified
5VoxelNetAP31.51—Unverified
#ModelMetricClaimedVerifiedStatus
1Frustrum-PointPillarsAP52.23—Unverified
2Frustum PointNetsAP50.22—Unverified
3Frustum PointNetsAP42.15—Unverified
4VoxelNetAP40.74—Unverified
5VoxelNetAP33.69—Unverified
#ModelMetricClaimedVerifiedStatus
1VoxelNetAP77.39—Unverified
2Frustum PointNetsAP75.33—Unverified
3Frustum PointNetsAP62.19—Unverified
4VoxelNetAP57.73—Unverified
#ModelMetricClaimedVerifiedStatus
1Frustum PointNetsAP75.38—Unverified
2Frustum PointNetsAP71.96—Unverified
3VoxelNetAP66.7—Unverified
4VoxelNetAP61.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Frustum PointNetsAP61.96—Unverified
2Frustum PointNetsAP56.77—Unverified
3VoxelNetAP54.76—Unverified
4VoxelNetAP48.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Frustum PointNetsAP58.09—Unverified
2Frustum PointNetsAP51.21—Unverified
3VoxelNetAP46.13—Unverified
4VoxelNetAP39.48—Unverified
#ModelMetricClaimedVerifiedStatus
1Unified-IOXLLocalization (ablation)67—Unverified
2GPV-2Localization (ablation)53.6—Unverified
3Mask R-CNNLocalization (ablation)44.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Frustum PointNetsAP54.68—Unverified
2VoxelNeAP50.55—Unverified
3Frustum PointNetsAP50.39—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT4-Vision 4-shot+CoTAccuracy49.7—Unverified
2Gemini-Pro 4-shot+CoTAccuracy33.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Frustum PointNetsAP84—Unverified
2VoxelNetAP79.26—Unverified
#ModelMetricClaimedVerifiedStatus
1Frustrum-PointPillarsAP60.98—Unverified
#ModelMetricClaimedVerifiedStatus
1Hausdorff LossPrecision88.1—Unverified
#ModelMetricClaimedVerifiedStatus
1oursCorLoc41.2—Unverified
#ModelMetricClaimedVerifiedStatus
1oursCorLoc47.45—Unverified
#ModelMetricClaimedVerifiedStatus
1Hausdorff LossF-Score88.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Hausdorff LossRecall89.2—Unverified