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 401–450 of 617 papers

TitleStatusHype
Parts-Based Articulated Object Localization in Clutter Using Belief Propagation—0
Entropy Guided Adversarial Model for Weakly Supervised Object Localization—0
Rethinking Class Activation Mapping for Weakly Supervised Object LocalizationCode1
Eigen-CAM: Class Activation Map using Principal ComponentsCode1
Object-Aware Centroid Voting for Monocular 3D Object Detection—0
A Generic Visualization Approach for Convolutional Neural NetworksCode1
Geometry Constrained Weakly Supervised Object LocalizationCode1
RepPoints V2: Verification Meets Regression for Object DetectionCode1
Training Interpretable Convolutional Neural Networks by Differentiating Class-specific FiltersCode1
Cross-Modal Weighting Network for RGB-D Salient Object DetectionCode1
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and DatasetsCode1
Mining Cross-Image Semantics for Weakly Supervised Semantic SegmentationCode1
Learning to Segment from Scribbles using Multi-scale Adversarial Attention GatesCode1
MoNet3D: Towards Accurate Monocular 3D Object Localization in Real TimeCode1
BOUNDARY REGULARIZED BUILDING FOOTPRINT EXTRACTION FROM SATELLITE IMAGES USING DEEP NEURAL NETWORKS—0
Boundary Regularized Building Footprint Extraction From Satellite Images Using Deep Neural Network—0
Rethinking Localization Map: Towards Accurate Object Perception with Self-Enhancement MapsCode0
Erasing Integrated Learning: A Simple Yet Effective Approach for Weakly Supervised Object Localization—0
Offset Bin Classification Network for Accurate Object Detection—0
Salient Object Detection Combining a Self-attention Module and a Feature Pyramid Network—0
Distilling Knowledge from Refinement in Multiple Instance Detection NetworksCode1
Spatio-temporal Tubelet Feature Aggregation and Object Linking in Videos—0
How spatial frequencies and color drive object search in real-world scenes: A new eye-movement corpus—0
Rethinking Object Detection in Retail StoresCode0
Pairwise Similarity Knowledge Transfer for Weakly Supervised Object LocalizationCode0
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAICode1
StarNet: towards Weakly Supervised Few-Shot Object DetectionCode0
PBRnet: Pyramidal Bounding Box Refinement to Improve Object Localization Accuracy—0
Dual-attention Guided Dropblock Module for Weakly Supervised Object LocalizationCode1
Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference—0
Weakly-supervised Object Localization for Few-shot Learning and Fine-grained Few-shot Learning—0
Hand-Priming in Object Localization for Assistive Egocentric Vision—0
Rethinking the Route Towards Weakly Supervised Object LocalizationCode1
Understanding the effects of artifacts on automated polyp detection and incorporating that knowledge via learning without forgettingCode0
Evaluating Weakly Supervised Object Localization Methods RightCode1
A Markerless Deep Learning-based 6 Degrees of Freedom PoseEstimation for with Mobile Robots using RGB Data—0
Extending Class Activation Mapping Using Gaussian Receptive Field—0
Deep Snake for Real-Time Instance SegmentationCode2
ScanRefer: 3D Object Localization in RGB-D Scans using Natural LanguageCode0
Convolutional STN for Weakly Supervised Object LocalizationCode0
IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection—0
Attributional Robustness Training using Input-Gradient Spatial AlignmentCode0
Sub-frame Appearance and 6D Pose Estimation of Fast Moving ObjectsCode0
Deep Mixture Density Network for Probabilistic Object Detection—0
Improve CAM with Auto-adapted Segmentation and Co-supervised Augmentation—0
Self-supervised Moving Vehicle Tracking with Stereo Sound—0
Towards Best Practice in Explaining Neural Network Decisions with LRPCode0
Deep Contextual Attention for Human-Object Interaction Detection—0
Combinational Class Activation Maps for Weakly Supervised Object LocalizationCode0
Explaining image classifiers by removing input features using generative modelsCode0
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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