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 41–50 of 617 papers

Title	Date	Tasks	Status	Hype
Audio-Visual Grouping Network for Sound Localization from Mixtures	Mar 29, 2023	Object LocalizationSound Source Localization	CodeCode Available	1
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation	Mar 20, 2022	image-classificationImage Classification	CodeCode Available	1
CLIP the Gap: A Single Domain Generalization Approach for Object Detection	Jan 13, 2023	Domain Generalizationimage-classification	CodeCode Available	1
Context-Aware Entity Grounding with Open-Vocabulary 3D Scene Graphs	Sep 27, 2023	FormNavigate	CodeCode Available	1
CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching	Mar 23, 2023	Described Object Detectionobject-detection	CodeCode Available	1
Boosting Segment Anything Model Towards Open-Vocabulary Learning	Dec 6, 2023	modelObject	CodeCode Available	1
Agent Journey Beyond RGB: Unveiling Hybrid Semantic-Spatial Environmental Representations for Vision-and-Language Navigation	Dec 9, 2024	Object LocalizationVision and Language Navigation	CodeCode Available	1
Background Activation Suppression for Weakly Supervised Object Localization	Dec 1, 2021	ObjectObject Localization	CodeCode Available	1
Background Activation Suppression for Weakly Supervised Object Localization and Semantic Segmentation	Sep 22, 2023	ObjectObject Localization	CodeCode Available	1
CLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic Segmentation For-Free	Sep 25, 2023	Image SegmentationObject Localization	CodeCode Available	1

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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