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 201–250 of 617 papers

TitleStatusHype
Adaptive Label Smoothing—0
Foreground Activation Maps for Weakly Supervised Object Localization—0
Learning Object Localization and 6D Pose Estimation from Simulation and Weakly Labeled Real Images—0
Could We Generate Cytology Images from Histopathology Images? An Empirical Study—0
A Markerless Deep Learning-based 6 Degrees of Freedom PoseEstimation for with Mobile Robots using RGB Data—0
Flash Photography for Data-Driven Hidden Scene Recovery—0
FingerSLAM: Closed-loop Unknown Object Localization and Reconstruction from Visuo-tactile Feedback—0
Learning Multi-Modal Class-Specific Tokens for Weakly Supervised Dense Object Localization—0
Learning task-agnostic representation via toddler-inspired learning—0
Learning to Detect Instance-level Salient Objects Using Complementary Image Labels—0
LocPoseNet: Robust Location Prior for Unseen Object Pose Estimation—0
Fine-Grained Attention for Weakly Supervised Object Localization—0
Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localization—0
FPAN: Fine-grained and Progressive Attention Localization Network for Data Retrieval—0
Finding Fallen Objects Via Asynchronous Audio-Visual Integration—0
Few-shot Weakly-Supervised Object Detection via Directional Statistics—0
Cooperative Multi-Monostatic Sensing for Object Localization in 6G Networks—0
Adapting Mask-RCNN for Automatic Nucleus Segmentation—0
Weakly-supervised Object Localization for Few-shot Learning and Fine-grained Few-shot Learning—0
Gaussian Processes with Context-Supported Priors for Active Object Localization—0
Generative Adversarial Networks for Unsupervised Object Co-localization—0
Few-shot Geometry-Aware Keypoint Localization—0
3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-scale 3D Point Clouds—0
Learning from Web Data: the Benefit of Unsupervised Object Localization—0
AV-SAM: Segment Anything Model Meets Audio-Visual Localization and Segmentation—0
FAST-Splat: Fast, Ambiguity-Free Semantics Transfer in Gaussian Splatting—0
1-HKUST: Object Detection in ILSVRC 2014—0
GLRD: Global-Local Collaborative Reason and Debate with PSL for 3D Open-Vocabulary Detection—0
Cyclic Learning for Binaural Audio Generation and Localization—0
GP-select: Accelerating EM using adaptive subspace preselection—0
Fast On-Line Kernel Density Estimation for Active Object Localization—0
D2DF2WOD: Learning Object Proposals for Weakly-Supervised Object Detection via Progressive Domain Adaptation—0
FAST OBJECT LOCALIZATION VIA SENSITIVITY ANALYSIS—0
Adaptively Denoising Proposal Collection forWeakly Supervised Object Localization—0
Fast Object Localization Using a CNN Feature Map Based Multi-Scale Search—0
Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection—0
Grounding Scene Graphs on Natural Images via Visio-Lingual Message Passing—0
Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels—0
Learning Instance Activation Maps for Weakly Supervised Instance Segmentation—0
Learning to Grasp Without Seeing—0
Extending Class Activation Mapping Using Gaussian Receptive Field—0
Heterogeneous Grid Convolution for Adaptive, Efficient, and Controllable Computation—0
Constrained Sampling for Class-Agnostic Weakly Supervised Object Localization—0
Deep Contextual Attention for Human-Object Interaction Detection—0
Exploring to learn visual saliency: The RL-IAC approach—0
HiLM-D: Towards High-Resolution Understanding in Multimodal Large Language Models for Autonomous Driving—0
Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation—0
Confidence-driven Bounding Box Localization for Small Object Detection—0
AuxDepthNet: Real-Time Monocular 3D Object Detection with Depth-Sensitive Features—0
Auto-Prompting SAM for Weakly Supervised Landslide Extraction—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