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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 426–450 of 617 papers

Title	Date	Tasks	Status	Hype
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI	Mar 16, 2020	BenchmarkingExplainable Artificial Intelligence (XAI)	CodeCode Available	1
StarNet: towards Weakly Supervised Few-Shot Object Detection	Mar 15, 2020	ClassificationFew-Shot Learning	CodeCode Available	0
PBRnet: Pyramidal Bounding Box Refinement to Improve Object Localization Accuracy	Mar 10, 2020	Object Localization	—Unverified	0
Dual-attention Guided Dropblock Module for Weakly Supervised Object Localization	Mar 9, 2020	Object LocalizationWeakly-Supervised Object Localization	CodeCode Available	1
Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference	Mar 5, 2020	Causal InferenceObject	—Unverified	0
Weakly-supervised Object Localization for Few-shot Learning and Fine-grained Few-shot Learning	Mar 2, 2020	ClassificationFew-Shot Learning	—Unverified	0
Hand-Priming in Object Localization for Assistive Egocentric Vision	Feb 28, 2020	Hand SegmentationMulti-Task Learning	—Unverified	0
Rethinking the Route Towards Weakly Supervised Object Localization	Feb 26, 2020	General ClassificationObject	CodeCode Available	1
Understanding the effects of artifacts on automated polyp detection and incorporating that knowledge via learning without forgetting	Feb 7, 2020	Object Localization	CodeCode Available	0
Evaluating Weakly Supervised Object Localization Methods Right	Jan 21, 2020	Few-Shot LearningModel Selection	CodeCode Available	1
A Markerless Deep Learning-based 6 Degrees of Freedom PoseEstimation for with Mobile Robots using RGB Data	Jan 16, 2020	Data VisualizationObject Localization	—Unverified	0
Extending Class Activation Mapping Using Gaussian Receptive Field	Jan 15, 2020	Deep LearningImage Classification	—Unverified	0
Deep Snake for Real-Time Instance Segmentation	Jan 6, 2020	GPUInstance Segmentation	CodeCode Available	2
ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language	Dec 18, 2019	ObjectObject Localization	CodeCode Available	0
Convolutional STN for Weakly Supervised Object Localization	Dec 3, 2019	ObjectObject Localization	CodeCode Available	0
IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection	Dec 2, 2019	Objectobject-detection	—Unverified	0
Attributional Robustness Training using Input-Gradient Spatial Alignment	Nov 29, 2019	BIG-bench Machine LearningObject Localization	CodeCode Available	0
Sub-frame Appearance and 6D Pose Estimation of Fast Moving Objects	Nov 25, 2019	6D Pose EstimationDeblurring	CodeCode Available	0
Deep Mixture Density Network for Probabilistic Object Detection	Nov 24, 2019	Objectobject-detection	—Unverified	0
Improve CAM with Auto-adapted Segmentation and Co-supervised Augmentation	Nov 17, 2019	ObjectObject Localization	—Unverified	0
Self-supervised Moving Vehicle Tracking with Stereo Sound	Oct 25, 2019	Object Localizationvehicle detection	—Unverified	0
Towards Best Practice in Explaining Neural Network Decisions with LRP	Oct 22, 2019	Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)	CodeCode Available	0
Deep Contextual Attention for Human-Object Interaction Detection	Oct 17, 2019	Human-Object Interaction DetectionObject	—Unverified	0
Combinational Class Activation Maps for Weakly Supervised Object Localization	Oct 12, 2019	ObjectObject Localization	CodeCode Available	0
Explaining image classifiers by removing input features using generative models	Oct 9, 2019	counterfactualObject Localization	CodeCode Available	0

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All datasets REVERIE KITTI Cars Easy KITTI Pedestrians Hard KITTI Pedestrians Moderate KITTI Cars Hard KITTI Cyclists Easy KITTI Cyclists Moderate KITTI Pedestrians Easy GRIT KITTI Cyclists Hard IllusionVQA KITTI Cars Moderate

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	OSMaN	RGSPL	32.99	—	Unverified
2	SUSA	RGSPL	27.31	—	Unverified
3	Shanks	RGSPL	22.85	—	Unverified
4	CVPR22	RGSPL	22.06	—	Unverified
5	damm1	RGSPL	15.96	—	Unverified
6	1637	RGSPL	14.03	—	Unverified
7	init. PREVALENT	RGSPL	13.51	—	Unverified
8	Airbert	RGSPL	13.28	—	Unverified
9	init. OSCAR	RGSPL	10	—	Unverified
10	SIA	RGSPL	9.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VoxelNet	AP	89.35	—	Unverified
2	VoxelNet	AP	89.35	—	Unverified
3	Frustum PointNets	AP	88.7	—	Unverified
4	Frustum PointNets	AP	81.2	—	Unverified
5	VoxelNet	AP	77.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Frustrum-PointPillars	AP	48.3	—	Unverified
2	Frustum PointNets	AP	47.2	—	Unverified
3	Frustum PointNets	AP	40.23	—	Unverified
4	VoxelNet	AP	38.11	—	Unverified
5	VoxelNet	AP	31.51	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Frustrum-PointPillars	AP	52.23	—	Unverified
2	Frustum PointNets	AP	50.22	—	Unverified
3	Frustum PointNets	AP	42.15	—	Unverified
4	VoxelNet	AP	40.74	—	Unverified
5	VoxelNet	AP	33.69	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VoxelNet	AP	77.39	—	Unverified
2	Frustum PointNets	AP	75.33	—	Unverified
3	Frustum PointNets	AP	62.19	—	Unverified
4	VoxelNet	AP	57.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Frustum PointNets	AP	75.38	—	Unverified
2	Frustum PointNets	AP	71.96	—	Unverified
3	VoxelNet	AP	66.7	—	Unverified
4	VoxelNet	AP	61.22	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Frustum PointNets	AP	61.96	—	Unverified
2	Frustum PointNets	AP	56.77	—	Unverified
3	VoxelNet	AP	54.76	—	Unverified
4	VoxelNet	AP	48.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Frustum PointNets	AP	58.09	—	Unverified
2	Frustum PointNets	AP	51.21	—	Unverified
3	VoxelNet	AP	46.13	—	Unverified
4	VoxelNet	AP	39.48	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Unified-IOXL	Localization (ablation)	67	—	Unverified
2	GPV-2	Localization (ablation)	53.6	—	Unverified
3	Mask R-CNN	Localization (ablation)	44.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Frustum PointNets	AP	54.68	—	Unverified
2	VoxelNe	AP	50.55	—	Unverified
3	Frustum PointNets	AP	50.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GPT4-Vision 4-shot+CoT	Accuracy	49.7	—	Unverified
2	Gemini-Pro 4-shot+CoT	Accuracy	33.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Frustum PointNets	AP	84	—	Unverified
2	VoxelNet	AP	79.26	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Frustrum-PointPillars	AP	60.98	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Hausdorff Loss	Precision	88.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ours	CorLoc	41.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ours	CorLoc	47.45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Hausdorff Loss	F-Score	88.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Hausdorff Loss	Recall	89.2	—	Unverified