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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 617 papers

TitleStatusHype
Distilling Knowledge from Refinement in Multiple Instance Detection NetworksCode1
A Generic Visualization Approach for Convolutional Neural NetworksCode1
Keep CALM and Improve Visual Feature AttributionCode1
IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language ModelsCode1
Integrated Grad-CAM: Sensitivity-Aware Visual Explanation of Deep Convolutional Networks via Integrated Gradient-Based ScoringCode1
TDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNsCode1
Recognizing Vector Graphics without RasterizationCode1
InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual ReferringCode1
Transfer learning for time series classificationCode1
Dual-attention Guided Dropblock Module for Weakly Supervised Object LocalizationCode1
Dual Attention U-Net with Feature Infusion: Pushing the Boundaries of Multiclass Defect SegmentationCode1
Agent Journey Beyond RGB: Unveiling Hybrid Semantic-Spatial Environmental Representations for Vision-and-Language NavigationCode1
Dual Progressive Transformations for Weakly Supervised Semantic SegmentationCode1
Context-Aware Entity Grounding with Open-Vocabulary 3D Scene GraphsCode1
Learning Deep Features for Discriminative LocalizationCode1
EDN: Salient Object Detection via Extremely-Downsampled NetworkCode1
Efficient Object Localization Using Convolutional NetworksCode1
Egocentric Audio-Visual Object LocalizationCode1
Deep Learning for Identifying Iran's Cultural Heritage Buildings in Need of Conservation Using Image Classification and Grad-CAMCode0
Progressive Representation Adaptation for Weakly Supervised Object LocalizationCode0
PixelCAM: Pixel Class Activation Mapping for Histology Image Classification and ROI LocalizationCode0
DAP: Detection-Aware Pre-training with Weak SupervisionCode0
DANet: Divergent Activation for Weakly Supervised Object LocalizationCode0
PEEKABOO: Hiding parts of an image for unsupervised object localizationCode0
Trade-offs in Fine-tuned Diffusion Models Between Accuracy and InterpretabilityCode0
3-Dimensional Sonic Phase-invariant Echo LocalizationCode0
Personal Fixations-Based Object Segmentation with Object Localization and Boundary PreservationCode0
Count-ception: Counting by Fully Convolutional Redundant CountingCode0
Co-Segmentation without any Pixel-level Supervision with Application to Large-Scale Sketch ClassificationCode0
One-Shot General Object LocalizationCode0
Attributional Robustness Training using Input-Gradient Spatial AlignmentCode0
Background-aware Classification Activation Map for Weakly Supervised Object LocalizationCode0
ALWOD: Active Learning for Weakly-Supervised Object DetectionCode0
Convolutional STN for Weakly Supervised Object LocalizationCode0
Object detection via a multi-region & semantic segmentation-aware CNN modelCode0
Contrastive Corpus Attribution for Explaining RepresentationsCode0
Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in VideoCode0
ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised LocalizationCode0
Multispectral Detection Transformer with Infrared-Centric Sensor FusionCode0
Object Detection via a Multi-Region and Semantic Segmentation-Aware CNN ModelCode0
Object Detectors Emerge in Deep Scene CNNsCode0
QUB-PHEO: A Visual-Based Dyadic Multi-View Dataset for Intention Inference in Collaborative AssemblyCode0
Min-Entropy Latent Model for Weakly Supervised Object DetectionCode0
Explaining Multi-modal Large Language Models by Analyzing their Vision PerceptionCode0
Concept Visualization: Explaining the CLIP Multi-modal Embedding Using WordNetCode0
Expeditious Saliency-guided Mix-up through Random Gradient ThresholdingCode0
Evaluation of Audio-Visual Alignments in Visually Grounded Speech ModelsCode0
All-pairs Consistency Learning for Weakly Supervised Semantic SegmentationCode0
MB-ORES: A Multi-Branch Object Reasoner for Visual Grounding in Remote SensingCode0
Evaluation and Comparison of Visual Language Models for Transportation Engineering ProblemsCode0
Show:102550
← PrevPage 4 of 13Next →
All datasetsREVERIEKITTI Cars EasyKITTI Pedestrians HardKITTI Pedestrians ModerateKITTI Cars HardKITTI Cyclists EasyKITTI Cyclists ModerateKITTI Pedestrians EasyGRITKITTI Cyclists HardIllusionVQAKITTI Cars Moderate

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